A5029485281- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Functional Brain Connectivity Studies
- Medical Image Segmentation Techniques
- Medical Imaging Techniques and Applications
- MRI in cancer diagnosis
- Radiomics and Machine Learning in Medical Imaging
- Fetal and Pediatric Neurological Disorders
- Optical Coherence Tomography Applications
- NMR spectroscopy and applications
- Neural dynamics and brain function
- Brain Tumor Detection and Classification
- Cardiac Imaging and Diagnostics
- Advanced Electron Microscopy Techniques and Applications
- Bone and Joint Diseases
- Visual perception and processing mechanisms
- Advanced Graph Neural Networks
- Digital Image Processing Techniques
- Dementia and Cognitive Impairment Research
- Advanced Vision and Imaging
- Advanced X-ray Imaging Techniques
- Retinal Development and Disorders
- Glaucoma and retinal disorders
- Advanced X-ray and CT Imaging
- Advanced Neural Network Applications
Harvard University
2015-2025
Massachusetts General Hospital
2015-2025
Athinoula A. Martinos Center for Biomedical Imaging
2015-2025
Boston University
2016-2024
Vassar College
2020-2021
Massachusetts Institute of Technology
2013-2021
Harvard University Press
2015
Decision Systems (United States)
2013
University of Minnesota
2007-2011
University of California, Los Angeles
2011
Abstract q‐Ball imaging is a high‐angular‐resolution diffusion technique that has been proven very successful in resolving multiple intravoxel fiber orientations MR images. The standard computation of the orientation distribution function (the probability given direction) from q‐ball data uses linear radial projection, neglecting change volume element along each direction. This results spherical distributions are different true functions. For instance, they neither normalized nor as sharp...
Significance We describe a readily exportable method for noninvasive imaging of the pancreatic inflammation underlying type-1 diabetes (T1D), based on MRI clinically approved magnetic nanoparticle ferumoxytol. This approach, which reflects uptake by macrophages in inflamed lesion, has been validated rigorously mouse T1D models. Methodological advances reported here include extensive optimization image acquisition and improved registration visualization technologies. A proof-of-principle...
Image segmentation is a critical step in numerous medical imaging studies, which can be facilitated by automatic computational techniques. Supervised methods, although highly effective, require large training datasets of manually labeled images that are labor-intensive to produce. Unsupervised on the contrary, used absence data segment new images. We introduce approach unsupervised image based computation local center mass. propose an efficient method group pixels one-dimensional signal, we...
Q-ball imaging (QBI) is a high angular resolution diffusion (HARDI) technique which has been proven very successful in resolving multiple intravoxel fiber orientations MR images. The standard computation of the orientation distribution function (ODF, probability given direction) from q-ball uses linear radial projection, neglecting change volume element along ray, thereby resulting distributions different true ODFs. For instance, they are not normalized or as sharp expected, and generally...
Purpose To describe an unsupervised three-dimensional cardiac motion estimation network (CarMEN) for deformable from two-dimensional cine MR images. Materials and Methods A function was implemented using CarMEN, a convolutional neural that takes two input volumes outputs field. smoothness constraint imposed on the field by regularizing Frobenius norm of its Jacobian matrix. CarMEN trained tested with data 150 patients who underwent MRI examinations validated synthetic (n = 100) pediatric 33)...
Abstract Estimating the thickness of cerebral cortex is a key step in many brain imaging studies, revealing valuable information on development or disease progression. In this work, we present framework for measuring cortical thickness, based minimizing line integrals over probability map gray matter MRI volume. We first prepare that contains each voxel belonging to matter. Then, basically defined as minimum integral segments centered at point interest. contrast our approach, previous...
Cortical connectivity is associated with cognitive and behavioral traits that are thought to vary between sexes. Using high-angular resolution diffusion imaging at 4 Tesla, we scanned 234 young adult twins siblings (mean age: 23.4 ± 2.0 SD years) 94 diffusion-encoding directions. We applied a novel Hough transform method extract fiber tracts throughout the entire brain, based on fields of constant solid angle orientation distribution functions (ODFs). surfaces were generated from each...
Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas large disregarded for probing white (WM). This unbalanced treatment part due to controversies relation the nature of blood oxygenation level-dependent (BOLD) contrast WM and its detectability. However, an accumulating body studies provided solid evidence significance BOLD signal revealed that it exhibits anisotropic spatio-temporal correlations...
We show that image registration using conventional interpolation and summation approximations of continuous integrals can generally fail because resampling artifacts. These artifacts negatively affect the accuracy by producing local optima, altering gradient, shifting global optimum, making rigid asymmetric. In this paper, after an extensive literature review, we demonstrate causes comparing inclusion avoidance analytically. sum-of-squared-differences cost function formulated as integral to...
The locus coeruleus (LC) is a key brain structure implicated in cognitive function and neurodegenerative disease. Automatic segmentation of the LC crucial step quantitative non-invasive analysis large MRI cohorts. Most publicly available imaging databases for training automatic models take advantage specialized contrast-enhancing (e.g., neuromelanin-sensitive) MRI. Segmentation developed with such image contrasts, however, are not readily applicable to existing datasets conventional...
We tackle the prediction of age and mini-mental state examination (MMSE) score based on structural brain connectivity derived from diffusion magnetic resonance images. propose a machine-learning model inspired by graph convolutional networks (GCNs), which takes input processes data separately through parallel GCN mechanism with multiple branches, thereby disentangling node features. The novelty our work lies in architecture, especially attention module, learns an embedding representation...
Despite their importance in shaping visual perception, functional connectivity between ocular dominance columns (ODCs), the building blocks of neuronal processing within human primary cortex (V1), remains largely unknown. Using high-resolution MRI (fMRI), we localized ODCs and assessed resting-state (rs-FC) 11 adults (3 females). Consistent with anatomical studies animals, found stronger rs-FC middle compared to deep superficial cortical depths selectively alike unalike polarity. Beyond what...
Purpose: To compare and evaluate the use of super‐resolution reconstruction (SRR), in frequency, image, wavelet domains, to reduce through‐plane partial voluming effects magnetic resonance imaging. Methods: The an isotropic high‐resolution image from multiple thick‐slice scans has been investigated through techniques domains. Experiments were carried out with T2‐weighted fast spin echo sequence on Academic College Radiology MRI phantom, where reconstructed images compared a reference scan...
Diffusion tensor imaging has accelerated the study of brain connectivity, but single-tensor diffusion models are too simplistic to model fiber crossing and mixing. Hybrid (HYDI) samples radial angular structure local on multiple spherical shells in q-space, combining high SNR CNR achievable at low b-values, respectively. We acquired analyzed human multi-shell HARDI ultra-high field-strength (7 Tesla; b=1000, 2000, 3000 s/mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML"...
Hardware constraints, scanning time limitations, patient movement, and signal-to-noise ratio (SNR) considerations, restrict the slice-selection in-plane resolutions of MRI differently, generally resulting in anisotropic voxels. This nonuniform sampling can be problematic, especially image segmentation clinical examination. To alleviate this, acquisition is divided into (two or) three separate scans, with higher thick slices, yet orthogonal directions. In this work, a noniterative...
In this paper we present a novel label fusion algorithm suited for scenarios in which different manual delineation protocols with potentially disparate structures have been used to annotate the training scans (hereafter referred as "atlases"). Such arise when atlases missing structures, they labeled levels of detail, or taken from heterogeneous databases. The proposed can be automatically scan any data. Further, it enables us generate new labels that are not protocol by defining...