Multimodal imaging. Medical search. Frequent questions

Responding to concerns regarding the growth of cardiac testing, the American College of Cardiology Foundation (ACCF) published Appropriate Use Criteria (AUC) for various cardiac imaging modalities. (medscape.com)
Single modality cardiac imaging appropriateness has been reported but there have been no studies assessing the appropriateness of multiple imaging modalities in an inpatient environment. (medscape.com)
The ACCF AUC captured the vast majority of clinical scenarios for multiple cardiac imaging modalities in this multi-centered study on Cardiology and GIM inpatients in the acute care setting. (medscape.com)
The rate of appropriate ordering was high across all imaging modalities. (medscape.com)
Recent methodological developments allow for the integration of information across imaging modalities, potentially yielding a more coherent view regarding the biology underlying the disorder. (nih.gov)
Diffusion and structural MRI data were fused to form imaging markers reflecting independent components that explain variation across modalities. (nih.gov)
No dominant imaging modality or marker characterizes structural brain phenotypes in adults with ADHD, but we can refine our characterization of the disorder by the integration of small effects across modalities. (nih.gov)
Data such as those represented by the Visible Human Project data often include multiple modalities such as color channels, multiple pulse sequences of magnetic resonance imaging, and X-ray CT data. (nih.gov)
Combined imaging modalities such as those described here can provide sensitive measures of monitoring retinal structure and function in patients with CHM. (nih.gov)
Multimodal image registration facilitates the combination of complementary information from images acquired with different modalities. (harvard.edu)
In medical imaging it is common practice to acquire a wide range of modalities (MRI, CT, PET, etc.), to highlight different structures or pathologies. (ucl.ac.uk)
In this thesis, I demonstrate for the first time that MM-OCT can be used as a complimentary technique to wide field imaging modalities, such as magnetic resonance imaging (MRI) or fluorescence imaging, using targeted multi-modal protein microspheres. (illinois.edu)
By using a single contrast agent to bridge the wide field and microscopic imaging modalities, a wide field imaging technique can be used to initially localize the contrast agent at the site of interest to guide the location of the MM-OCT imaging to provide a microscopic view. (illinois.edu)
The application of multiple imaging modalities has enabled the discovery of GRBs on different resolution scales, generating a detailed description of GRB structure and morphology. (gla.ac.uk)
Multimodal medical image fusion, as a powerful tool for the clinical applications, has developed with the advent of various imaging modalities in medical imaging. (myprojectbazaar.com)
Multi-modal generative AI involves the use of machine learning techniques to generate high-quality medical images from multiple sources and modalities, such as CT, MRI, and ultrasound scans. (nvidia.com)
In this review, we aimed to discuss the various imaging modalities and approaches used in the diagnosis and treatment of AIS. (j-stroke.org)
Correlative imaging using multiple multiscale modalities is particularly important to advance the understanding of placenta structure, function and their relationship. (bvsalud.org)
This paper presents a novel scheme to learn the mutual benefits of different modalities to achieve better segmentation results for unpaired multi-modal medical images. (midl.io)
In contrast, a direct model would learn a single multimodal space in which representations from the two modalities can be directly compared. (sun.ac.za)
For more information about the different imaging modalities contained within this instrument, click . (nih.gov)
Multimodal sentiment analysis is a technology for traditional text-based sentiment analysis, which includes modalities such as audio and visual data. (wikipedia.org)
Unlike the traditional text-based sentiment analysis, multimodal sentiment analysis undergo a fusion process in which data from different modalities (text, audio, or visual) are fused and analyzed together. (wikipedia.org)
Due to the subtle features characterizing RPD, multiple imaging modalities are often necessary to confirm the presence and extension of RPD, considerably increasing the workload of the expert graders. (diagnijmegen.nl)
Conducted on retinal images drawn from the Rotterdam Study, a population-based cohort, in three modalities: color fundus photographs (CFP), fundus autofluorescence images (FAF) and near-infrared reflectance images (NIR). (diagnijmegen.nl)
The model jointly inputs a set of co-registered retinal image modalities (CFP, NIR, FAF) and outputs a heatmap image containing, per pixel, the likelihood of RPD presence. (diagnijmegen.nl)
However, introducing other imaging modalities, such as OCT, might help diminish ambiguities in the classification and quantification of this abnormality. (diagnijmegen.nl)

The development, characterisation and testing of a novel all-optical, multi-modal preclinical biomedical imaging system is presented. (bham.ac.uk)
Here we employed a multi-modal correlative imaging approach to explore RSV cytoplasmic compartments during RSV infection, aiming to better understand RSV replication. (gla.ac.uk)
Facing the challenge of exploring and sharing multi-terabyte, multi-modal and multi-scale image data of heterogeneous dimensionality, we developed MoBIE, a Fiji plugin that provides rich visualization features to enable browsing data from numerous biomedical applications on a standard laptop computer. (biorxiv.org)
The problem of retrieving images from a database based on a multi-modal (image- text) query. (paperswithcode.com)
These models are helping clinicians and researchers streamline imaging workflows to uncover hidden insights, improve productivity, and connect multi-modal patient information for deeper understanding of disease. (nvidia.com)
Integrating multi-modal data to promote medical image analysis has recently gained great attention. (midl.io)

The Multimodal Imaging of Neurodegenerative Disease (MIND) Unit uses magnetic resonance (MR) and positron emission tomography (PET) neuroimaging in conjunction with epidemiologic, proteomic, and genetic methods to further understand the mechanisms underlying age-related neurodegenerative conditions such as Alzheimer's disease. (nih.gov)
Currently, the MIND Unit is using a multimodal neuroimaging approach to understand how chronic systemic inflammation, neuroinflammation, and vascular dysfunction influence the development and progression of the brain changes underlying Alzheimer's disease and late-life cognitive decline. (nih.gov)
Using multimodal neuroimaging to better understand human cognitive functions. (nih.gov)

The purpose of NTR is to develop, optimize, and validate imaging technology platforms and methods so that they can enter single or multi-site clinical trials and eventually be incorporated into clinical practice. (nih.gov)
Typically, statistical measurement is expected to be consistent over a local methods in image processing employ the distribution of neighborhood. (nih.gov)
The contrast enhancement methods for adaptive histogram image has uncorrelated Gaussian distributed additive equalization (AHE). (nih.gov)
Most existing methods require computation of the joint histogram of the images, while some perform joint segmentation and registration in alternate iterations. (harvard.edu)
We empirically evaluate our method via rigid registration of multicontrast brain images, and demonstrate an often higher registration accuracy in the results produced by the proposed technique, compared to those by several existing methods. (harvard.edu)
In addition, there is a lack of standardized imaging protocols and a variety of qualitative and quantitative (automated) methods for assessing cerebral perfusion in AIS [ 15 ]. (j-stroke.org)
International challenges have become the standard for validation of biomedical image analysis methods. (nature.com)

We analyzed a sample of adults with persistent ADHD and healthy controls using an advanced multimodal linked independent component analysis approach. (nih.gov)
In summary our registration approach seeks to maximize the image similarity given By denotes the control points and represent the index of the control point. (exposed-skin-care.net)
A multimodal approach to children's picturebooks focuses on how images and words (and their interactions) collaboratively make meaning. (ucsb.edu)
2011. A Generative Approach for Image-Based Modeling of Tumor Growth. (crossref.org)
1] observe that randomly sampling a latent code alone doesn't help with mode collapse, the proposed approach applies a cycle consistency loss on both the input-output image pairs and the latent code - output pairs via alternating joint optimization. (nips.cc)
Additionally, we propose multimodal classifier-free guidance which enables editing images using both reference images and text when using our approach with foundational diffusion models. (github.io)
This paper proposes an automatic spatially-aware concept discovery approach using weakly labeled image-text data from shopping websites. (paperswithcode.com)
Labeling Opportunities - This approach could also help build single-modal imaging databases, as its combination of eye-tracking and disease localization could be used to create automated image labeling workflows (during interpretations). (theimagingwire.com)
By leveraging the strengths of each modality, this approach can improve the accuracy of medical imaging and enable more accurate diagnoses and treatment planning. (nvidia.com)
The objective of the project SWAVE 2.0 was to understand human placental structure and function and thereby identify quantifiable measures of placental health using a multimodal correlative approach. (bvsalud.org)
Firstly, it compares unsupervised learning to transfer learning for an indirect multimodal few-shot matching approach on a dataset of paired isolated spoken and visual digits. (sun.ac.za)

No single imaging modality dominated this result. (nih.gov)
The CLIP model is not the first model that operates on joined image-text modality. (github.com)

This Funding Opportunity Announcement (FOA) issued by the National Cancer Institute (NCI) is an open competition initiative, designed to continue the efforts of the NCI to develop and translate cancer-relevant optical imaging technologies as a part of an overall imaging program for early cancer detection, diagnosis, therapeutic response, drug development, and image-guided therapy. (nih.gov)
In particular, with medical imaging, researchers are using computer vision to perform accurate early detection, medical classification, and advanced, automated 3D segmentation. (nvidia.com)
In radiology, machine learning algorithms and computer vision can help analyze medical images, aiding radiologists in the detection, diagnosis, and treatment of diseases. (nvidia.com)
The mission of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) is to transform, through technology development, our understanding of disease and its prevention, detection, diagnosis, and treatment. (nih.gov)
Cone photoreceptor cells imaged using annular pupil illumination combined with sub-Airy disk confocal pinhole detection. (nih.gov)
Confocal reflectance (top) and non-confocal split detection (bottom) images are simultaneously acquired in a living human eye. (nih.gov)
Confocal reflectance image (top) showing dark cones surrounded by reflective rods and non-confocal split detection image (bottom) showing the presence of cone photoreceptors at locations where dark cones are observed. (nih.gov)
With the extensive amount of social media data available online in different forms such as videos and images, the conventional text-based sentiment analysis has evolved into more complex models of multimodal sentiment analysis, which can be applied in the development of virtual assistants, analysis of YouTube movie reviews, analysis of news videos, and emotion recognition (sometimes known as emotion detection) such as depression monitoring, among others. (wikipedia.org)
The proposed DNN obtained an area under the receiver operating characteristic curve (AUROC) with 95% confidence interval (CI) of 0.939[0.818-1.0], a sensitivity (SE) of 0.928 and specificity (SP) of 0.809 for the detection of RPD in multimodal imaging. (diagnijmegen.nl)

Accordingly, all responses to this FOA will be considered new applications, with the main objective being to accelerate the translational research of in vivo multimodal imaging and/or spectroscopic platforms from the laboratory and pre-clinical level to the clinical level. (nih.gov)
Applicants responding to this FOA must identify a specific cancer-relevant clinical goal and propose to develop and validate at least one multimodal imaging platform, as defined in this FOA, to address this clinical goal. (nih.gov)
Applicants may submit more than one application, provided they are scientifically distinct (i.e., applications that address separate clinical cancer imaging problems and propose different technology platforms for development). (nih.gov)
In this thesis, I describe the design and construction of an intraoperative clinical OCT system that can be used to image and classify breast cancer tumor margins as normal, close, or positive. (illinois.edu)
Novarad - Transformational imaging technologies that empower hospitals and clinicians to deliver clinical, operational and fiscal excellence. (theimagingwire.com)
Nuclear Cardiology and Multimodal Cardiovascular Imaging is a one-stop, comprehensive guide to the diagnostic and clinical implications of this complex and increasingly important technology. (icebe.es)
A custom-built adaptive optics ophthalmoscope, located within the Eye Clinic of the NIH Clinical Center, was used to obtain all of the images in this image gallery. (nih.gov)
Automatic classification and quantification of RPD using deep learning on multimodal images will enable the automatic and accurate analysis of increasingly large amounts of data for clinical studies and will facilitate AMD screening in the elderly by decreasing the workload of the expert graders. (diagnijmegen.nl)

Enlarged retinal pigment epithelial cells (left half of image) labeled with indocyanine green dye in a patient with choroideremia. (nih.gov)
Disrupted retinal pigment epithelial cells visualized using darkfield imaging in choroideremia. (nih.gov)
Multimodal image of retinal pigment epithelial cells. (nih.gov)
Retinal pigment epithelial cells imaged noninvasively in a living human eye using adaptive optics. (nih.gov)
Cone photoreceptor neurons (red) and retinal pigment epithelial cells labeled using indocyanine green dye (green), imaged in a living human eye using adaptive optics. (nih.gov)
We propose a deep neural network (DNN) architecture that classifies and quantifies RPD using multimodal retinal images. (diagnijmegen.nl)
The proposed DNN showed promising capacities in the tasks of classifying and quantifying RPD lesions on multimodal retinal images. (diagnijmegen.nl)

The network will be called the "Network for Translational Research: Optical Imaging" (NTR). (nih.gov)
Fluorescently-labeled external limiting membrane encircling cone and rod photoreceptors, imaged using an adaptive optics translational imaging framework microscope. (nih.gov)

Preliminary results suggest the technology that improves the confidence of the clinicians with the multimodal imaging diagnostic. (unifi.it)
United Imaging - Our mission, Equal Healthcare for All, pushes us beyond conventional boundaries to help clinicians expand modern, digital, intelligent care to more people within their communities. (theimagingwire.com)
Current imaging protocols for acute stroke are dependent on the available resources and clinicians' preferences and experiences. (j-stroke.org)

Cardiac tests characterized were transthoracic echocardiography (TTE), transesophageal echocardiography (TEE), single-photon emission tomography myocardial perfusion imaging (SPECT), and diagnostic cardiac catheterization. (medscape.com)
We recommend further work towards improving appropriate utilization of cardiac imaging resources focus on the out-patient setting. (medscape.com)
We have demonstrated the effectiveness of the proposed method on two medical image segmentation scenarios: (1) cardiac structure segmentation, and (2) abdominal multi-organ segmentation. (midl.io)
Part of the Braunwald family of renowned cardiology references, it provides cutting-edge coverage of multimodal cardiac imaging along with case vignettes and integrated teaching content-ideal for cardiologists, cardiology fellows, radiologists, and nuclear medicine physicians. (icebe.es)

This paper introduces new work in multiscale image statistics, a local framework that supports adaptive measurement of image structure where data may be represented by multiple incommensurable values. (nih.gov)
The database provides framework for (1) rapid prototyping, (2) large scale batch processing of images and (3) scalable project management. (nih.gov)
The theoretical framework upon which this study is conducted incorporates Halliday's (1978) three metafunctions, and Kress and Van Leeuwen's (1996) adaptation of them for the analysis of images and their captions. (edu.pl)
2004. Analyzing Multimodal Interaction: A Methodological Framework. (edu.pl)
Experimental results and comparative study show that the proposed fusion framework provides an effective way to enable more accurate analysis of multimodality images. (myprojectbazaar.com)
The paper extends the pix2pix [1] framework of image-image translation by conditioning the generation of an image not only on an input image but also on a randomly sampled latent code. (nips.cc)
We propose PAIR Diffusion, a generic framework that can enable a diffusion model to control the structure and appearance properties of each object in the image. (github.io)
Our framework allows for various object-level editing operations on real images such as reference image-based appearance editing, free-form shape editing, adding objects, and variations. (github.io)
Learn how MONAI, a framework for building and deploying medical AI, and partners like King's College London, Mount Sinai, and East River Imaging are using generative AI to study disease and make AI decisions and predictions more accurate, trusted, and safe. (nvidia.com)

Such measurements have applications in nonlinear filtering, texture analysis, deformable registration and image segmentation. (nih.gov)
In this letter, we introduce a new non-information theoretical method for pairwise multimodal image registration, in which the error of segmentation-using both images-is considered as the registration cost function. (harvard.edu)
Deep learning assists in tasks such as image segmentation, tissue reconstruction, and disease classification to improve the accuracy and efficiency of pathological diagnosis. (nvidia.com)

IBM Research just released a multimodal chest X-ray dataset that could represent a major advancement from the datasets we use today. (theimagingwire.com)
The Multimodal Dataset - The 1,083-image dataset combines CXR images, radiologist eye-tracking recordings, localized disease labels, report text, and radiologist dictation audio - and the eye-tracking and dictation recordings are synced. (theimagingwire.com)
Next Step: Grow the Dataset - The researchers made their dataset and processes open-source, encouraging other groups to create similar datasets and help drive multimodal AI forward. (theimagingwire.com)

The ability to artificially-generate images can be used to efficiently create data for training deep learning algorithms. (nih.gov)

Meanwhile, researchers at the University of California-Irvine and the University of Southern California, having earlier reported what they believed to be the first probe to integrate OCT optical components with an ultrasound (US) transducer, have now used the device to demonstrate high-resolution coregistered intravascular imaging. (laserfocusworld.com)
The coaxial US and light beams are steered by a mirror, mounted at the head of the hybrid probe 45° relative to the light and the ultrasound beams to change their propagation directions, to enable US/OCT imaging simultaneously. (laserfocusworld.com)
The qualitative analysis showed good correlation between findings in the MRI, ultrasound and histopathology images. (bvsalud.org)

Summary: The paper enforces a cycle consistency between the latent code and the image output of a generative model that is applied to image-image translation problems. (nips.cc)
Generative image editing has recently witnessed extremely fast-paced growth. (github.io)
Generative AI for medical imaging can create infinite synthetic images of the human anatomy. (nvidia.com)
It may worth to mention the work on automatic image captioning with generative text models, vision part of which might display similar multimodal properties (which briefly mentioned in the footnote 4). (github.com)

Traditionally trained observers do lesion identification and quantification manually on each MRI image. (nih.gov)
Delineations of the areas affected with RPD were made in consensus by two human experts using CFP and NIR images simultaneously and were used as reference standard (RS) for RPD area quantification. (diagnijmegen.nl)

Researchers demonstrate critical improvements to functional Near Infrared Spectroscopy (fNIRS)-based optical imaging in the brain. (nih.gov)

Her research interests are multimodal stylistics and cognitive poetics of children's picturebooks. (ucsb.edu)

Spatial Frequency Domain Imaging (SFDI) is an optical method that has been shown to be a reliable method for physiology assessment - particularly for burn depth. (sbir.gov)
Multimodal pathology assessment of prostate cancer for precision medicine - a pilot study utilising next generation sequencing and image analysis. (ox.ac.uk)

Vanderbilt University Institute of Imaging Science Center for Computational Imaging XNAT: A multimodal data archive and processing environment. (nih.gov)
The research consists of the studying of the requirements of the end-user with the aim of presenting the multimodal data in an optimal way (using the available screen space, introducing different hardware solutions) and making it easily and fast accessible and usable (minimum number of click to access the certain functionality, touch screen usage). (unifi.it)
In this paper , we present a multimodal image acquisition protocol designed to acquire and align data from ex vivo placenta specimens derived from both healthy and complicated pregnancies . (bvsalud.org)
The existing approaches in multimodal sentiment analysis data fusion can be grouped into three main categories: feature-level, decision-level, and hybrid fusion, and the performance of the sentiment classification depends on which type of fusion technique is employed. (wikipedia.org)

Some of the most important audio features employed in multimodal sentiment analysis are mel-frequency cepstrum (MFCC), spectral centroid, spectral flux, beat histogram, beat sum, strongest beat, pause duration, and pitch. (wikipedia.org)

Similar to the traditional sentiment analysis, one of the most basic task in multimodal sentiment analysis is sentiment classification, which classifies different sentiments into categories such as positive, negative, or neutral. (wikipedia.org)

AI Model Opportunities - Multimodal datasets like this could allow AI developers to create more sophisticated and explainable AI models, while potentially leading to models that are better aligned with radiologists' actual diagnostic processes. (theimagingwire.com)

An OCT image, combined with spectroscopic autofluorescence information, depicts a colon. (laserfocusworld.com)

This image was obtained approximately 30 minutes after intravenous administration of 4.15 mCi of [18F]fluoro-2-deoxyglucose (FDG) to a 10-year-old boy with autism spectrum disorder and unspecified intellectual disabitliy using auto-attenuation with a 24-minute acquisition period. (medscape.com)
OASIS uses multimodal MRI from one image acquisition session and produces voxel-level probability maps of the brain that quantifies the likelihood that each voxel is part of a lesion. (nih.gov)
Project SWAVE 2.0: An overview of the study design for multimodal placental image acquisition and alignment. (bvsalud.org)

Specifically, smile, is considered to be one of the most predictive visual cues in multimodal sentiment analysis. (wikipedia.org)

Experiments on several datasets show the accuracy of the model and the fluency of the language it learns solely from image descriptions. (paperswithcode.com)

These investigations furthered the utility of the OCT technology for cancer imaging and diagnosis. (illinois.edu)
This program supports the development and application of optical imaging, microscopy, and spectroscopy techniques for improving disease prevention, diagnosis, and treatment in the medical office, at the bedside, or in the operating room. (nih.gov)
The goal of this STTR effort is to design a portable, multimodal, non-contact imaging system for burn depth diagnosis and tracking of wound healing. (sbir.gov)

HTN Hypertension, PCI Percutaneous Coronary Intervention, ACS acute coronary syndrome, CABG coronary artery by-pass graft, TTE transthoracic echocardiography, TEE transesophageal echocardiography, SPECT single-photon emission tomography myocardial perfusion imaging. (medscape.com)
This chapter discusses a combination of imaging techniques, including fundus-guided microperimetry, confocal and non-confocal adaptive optics scanning laser ophthalmoscopy (AOSLO), fundus autofluorescence (FAF), and swept-source optical coherence tomography angiography (SS-OCTA) to analyze macular sensitivity, cone photoreceptor outer and inner segment structure, RPE structure, and CC perfusion, respectively. (nih.gov)

The OASIS lesion segmentations are robust to changes in imaging centers and scanning parameters. (nih.gov)
However, advanced imaging is not widely available, particularly in low- or middle-income countries and primary stroke centers [ 12 ], and is potentially associated with treatment delay and increased cost [ 13 , 14 ]. (j-stroke.org)

To investigate the capability of multimodal imaging to evaluate treatment response to ICB therapy, hyperpolarized 13 C MRI using [1- 13 C] pyruvate and [1,4- 13 C2] fumarate and dynamic contrast enhanced (DCE) MRI was evaluated to detect early changes in tumor glycolysis, necrosis, and intratumor perfusion/permeability, respectively. (nih.gov)

Her research on stimulated Raman scattering (SRS) microscopy and its application to imaging cell metabolism earned her a coveted Blavatnik Young Investigator Award. (nyu.edu)
The method of the research is based on the contribute of the group of practical orthopedics involved in two stages of the study: collection of the requirements during the oral interviews and evaluation of the proposed imaging platform by execution of the specific tasks. (unifi.it)
In my research, I propose two new direct multimodal networks: a multimodal triplet network (MTriplet) which combines two triplet losses, and a multimodal correspondence autoencoder (MCAE) which combines two correspondence autoencoders (CAEs). (sun.ac.za)
Over time, research practice began to change, and the number of challenges organized annually has been increasing steadily (Fig. 1 a), with currently about 28 biomedical image analysis challenges with a mean of 4 tasks conducted annually. (nature.com)

PAIR Diffusion: A Comprehensive Multimodal Object-level Image Editor. (github.io)
PAIR diffusion achieves comprehensive editing capabilities in a multimodal manner by percieving images as composition of various objects. (github.io)

In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. (nature.com)
About one decade ago, a broader interest in biomedical challenge organization arose with the first grand challenge that was organized in the scope of the international conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2007 9 . (nature.com)
Overview of biomedical image analysis challenges. (nature.com)

Advances in functional and structural MR image analysis and implementation as FSL. (crossref.org)

The key principle of the imaging system is to use surface capture results to enhance the accuracy of DOT image reconstruction, and to use the results of both surface capture and DOT to enhance the accuracy of BLT. (bham.ac.uk)
The task is translating an image of domain A to another domain while making the results perceptually realistic and diverse. (nips.cc)

They used the integrated systems to image rabbit aorta in-vitro , and say that the combined US-OCT system demonstrated high resolution in visualizing superficial arterial structures while retaining the deep tissue penetration capability of ultrasonic imaging. (laserfocusworld.com)

In her most recent work, her team has transformed stimulated Raman scattering (SRS) microscopy into a super-resolution (~50nm) multimodal metabolic imaging platform. (nyu.edu)

From automating workflows to improving processing speed and image quality, there are numerous ways AI can help detect and diagnose disease. (nvidia.com)

The autofluorescence emission is red-shifted in the region of the tumor, in the center of the image. (laserfocusworld.com)

Medical Image Understanding and Analysis. (ucl.ac.uk)
In this notebook, we show how to use OpenAI GPT4V MultiModal LLM class/abstraction for image understanding/reasoning. (llamaindex.ai)

They also imaged the lipid and protein turnover rate and the metabolic heterogeneity in cells, animals, and human tissues. (nyu.edu)

As patient movement between scans or scanning session is unavoidable, registration is often an essential step before any subsequent image analysis. (ucl.ac.uk)
2006. Multimodal Transcription and Text Analysis: A Multimedia Toolkit and Coursebook. (edu.pl)
2014. "Multimodal Discourse Analysis. (edu.pl)
â A preliminary correlative imaging analysis for a placenta specimen is presented. (bvsalud.org)
In multimodal sentiment analysis, a combination of different textual, audio, and visual features are employed. (wikipedia.org)
Similar to the conventional text-based sentiment analysis, some of the most commonly used textual features in multimodal sentiment analysis are unigrams and n-grams, which are basically a sequence of words in a given textual document. (wikipedia.org)
Similar to text-based sentiment analysis, multimodal sentiment analysis can be applied in the development of different forms of recommender systems such as in the analysis of user-generated videos of movie reviews and general product reviews, to predict the sentiments of customers, and subsequently create product or service recommendations. (wikipedia.org)
a pilot study utilising next generation sequencing and image analysis. (ox.ac.uk)
This study aims to pilot evaluation of prostate cancer in a multimodal way, incorporating both next generation sequencing and image analysis. (ox.ac.uk)

In this paper, we introduce a cost function based on joint total variation for such multimodal image registration. (ucl.ac.uk)
Specifically we focus on the registration between a high-resolution image and a low-resolution image. (exposed-skin-care.net)
Preliminaries A. Maximization of Mutual Information In this section we describe the maximization of MI for multimodal image registration. (exposed-skin-care.net)
The underlying idea is usually to split the image into a set of nonoverlapping regions using the 3D Harris operator derived from the higher resolution image and to perform registration on spatially meaningful regions. (exposed-skin-care.net)
Using this modified MI the local structure matrices provide a geometric similarity measure while the image intensities continue to provide an appearance measure thereby allowing us to find correspondence more reliably and address the BCH limitation of the traditional MI-based registration. (exposed-skin-care.net)
The first known efforts to address this problem date back to the late 90 s 4 , when Jay West, J Michael Fitzpatrick and colleagues performed an international comparative evaluation on intermodality brain image registration techniques. (nature.com)

Cone photoreceptors imaged in a human eye using adaptive optics (left) and artificially-generated (fake) images of cone photoreceptors placed in the same locations where cones are present in the left image and matched to the same size/shape, using deep learning (right). (nih.gov)

Recently there have been many papers about learning conditional image distributions *without* domain alignments, using domain adversarial losses or cycle-consistency terms. (nips.cc)

Multiscale statistics can establish local correlations, covariances, and entropy measurements across the image. (nih.gov)

This FOA stems from the previous initiative on optical imaging technology (covered by RFA-CA-03-002 ). (nih.gov)
As with most other optical imaging techniques, there is a trade off between the imaging field of view and the high-resolution microscopic imaging. (illinois.edu)
This multi-molecular super-resolution optical imaging platform is non-invasive and universally applicable. (nyu.edu)
Researchers with support from NIBIB has developed an improved optical imaging technique that found differences between potentially life-threatening coronary plaques and those posing less imminent danger for patients with coronary artery disease. (nih.gov)

Anatomy22

Organisms1

Diseases20

Chemicals and Drugs38

Analytical, Diagnostic and Therapeutic Techniques and Equipment97

Psychiatry and Psychology39

Phenomena and Processes27

Disciplines and Occupations10

Technology, Industry, Agriculture14

Humanities3

Information Science19

Health Care21

Geographicals1

Modalities27

Multi-modal6

Neuroimaging3

Methods7

Approach11

Modality2

Detection9

Clinical8

Retinal7

Translational2

Clinicians3

Cardiac4

Framework9

Segmentation3

Dataset3

Algorithms1

Ultrasound3

Generative4

Quantification2

Near-infrared spe1

Cognitive1

Assessment2

Data4

Histogram1

Classifies1

Diagnostic1

Spectroscopic1

Acquisition3

Cues1

Datasets1

Diagnosis3

Tomography2

Centers2

Perfusion1

Research4

Diffusion2

Biomedical3

Functional1

Results2

Capability1

Microscopy1

Workflows1

Tumor1

Understanding2

Protein1

Analysis9

Registration6

Shape1

Losses1

Multiscale1

Optical Imaging4