Samuel W. Remedios
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View article: Diffusion-Driven Generation of Minimally Preprocessed Brain MRI
Diffusion-Driven Generation of Minimally Preprocessed Brain MRI Open
The purpose of this study is to present and compare three denoising diffusion probabilistic models (DDPMs) that generate 3D $T_1$-weighted MRI human brain images. Three DDPMs were trained using 80,675 image volumes from 42,406 subjects spa…
View article: MSRepaint: Multiple Sclerosis Repaint with Conditional Denoising Diffusion Implicit Model for Bidirectional Lesion Filling and Synthesis
MSRepaint: Multiple Sclerosis Repaint with Conditional Denoising Diffusion Implicit Model for Bidirectional Lesion Filling and Synthesis Open
In multiple sclerosis, lesions interfere with automated magnetic resonance imaging analyses such as brain parcellation and deformable registration, while lesion segmentation models are hindered by the limited availability of annotated trai…
View article: Segmenting Thalamic Nuclei: T1 Maps Provide a Reliable and Efficient Solution
Segmenting Thalamic Nuclei: T1 Maps Provide a Reliable and Efficient Solution Open
Accurate thalamic nuclei segmentation is crucial for understanding neurological diseases, brain functions, and guiding clinical interventions. However, the optimal inputs for segmentation remain unclear. This study systematically evaluates…
View article: The relationship of white matter tract orientation to vascular geometry in the human brain
The relationship of white matter tract orientation to vascular geometry in the human brain Open
View article: Influence of early through late fusion on pancreas segmentation from imperfectly registered multimodal magnetic resonance imaging
Influence of early through late fusion on pancreas segmentation from imperfectly registered multimodal magnetic resonance imaging Open
Fusion in specific blocks can improve performance, but the best blocks for fusion are model-specific, and the gains are small. In imperfectly registered datasets, fusion is a nuanced problem, with the art of design remaining vital for unco…
View article: The relationship of white matter tract orientation to vascular geometry in the human brain
The relationship of white matter tract orientation to vascular geometry in the human brain Open
The white matter of the human brain exhibits highly ordered anisotropic structures of both axonal nerve fibers and cerebral vasculature. Separately, the anisotropic nature of white matter axons and white matter vasculature have been shown …
View article: An evaluation of image-based and statistical techniques for harmonizing brain volume measurements
An evaluation of image-based and statistical techniques for harmonizing brain volume measurements Open
Volumetric analysis of magnetic resonance brain images is often complicated by variations in scanner hardware, software, and acquisition settings. Over the past several years, there has been an increase in the use of retrospective harmoniz…
View article: Super-resolution multi-contrast unbiased eye atlases with deep probabilistic refinement
Super-resolution multi-contrast unbiased eye atlases with deep probabilistic refinement Open
By combining super-resolution preprocessing and deep probabilistic models, we address the challenge of generating an eye atlas to serve as a standardized reference across a largely variable population.
View article: Data-driven nucleus subclassification on colon hematoxylin and eosin using style-transferred digital pathology
Data-driven nucleus subclassification on colon hematoxylin and eosin using style-transferred digital pathology Open
This is the first work to provide cell type classification for helper T and epithelial progenitor nuclei on H&E.
View article: Unique MS Lesion Identification from MRI
Unique MS Lesion Identification from MRI Open
Unique identification of multiple sclerosis (MS) white matter lesions (WMLs) is important to help characterize MS progression. WMLs are routinely identified from magnetic resonance images (MRIs) but the resultant total lesion load does not…
View article: Bi-Directional MS Lesion Filling and Synthesis Using Denoising Diffusion Implicit Model-based Lesion Repainting
Bi-Directional MS Lesion Filling and Synthesis Using Denoising Diffusion Implicit Model-based Lesion Repainting Open
Automatic magnetic resonance (MR) image processing pipelines are widely used to study people with multiple sclerosis (PwMS), encompassing tasks such as lesion segmentation and brain parcellation. However, the presence of lesion often compl…
View article: Influence of Early through Late Fusion on Pancreas Segmentation from Imperfectly Registered Multimodal MRI
Influence of Early through Late Fusion on Pancreas Segmentation from Imperfectly Registered Multimodal MRI Open
Multimodal fusion promises better pancreas segmentation. However, where to perform fusion in models is still an open question. It is unclear if there is a best location to fuse information when analyzing pairs of imperfectly aligned images…
View article: Beyond MR Image Harmonization: Resolution Matters Too
Beyond MR Image Harmonization: Resolution Matters Too Open
Magnetic resonance (MR) imaging is commonly used in the clinical setting to non-invasively monitor the body. There exists a large variability in MR imaging due to differences in scanner hardware, software, and protocol design. Ideally, a p…
View article: Data-driven Nucleus Subclassification on Colon H&E using Style-transferred Digital Pathology
Data-driven Nucleus Subclassification on Colon H&E using Style-transferred Digital Pathology Open
Understanding the way cells communicate, co-locate, and interrelate is essential to furthering our understanding of how the body functions. H&E is widely available, however, cell subtyping often requires expert knowledge and the use of spe…
View article: Pushing the limits of zero-shot self-supervised super-resolution of anisotropic MR images
Pushing the limits of zero-shot self-supervised super-resolution of anisotropic MR images Open
Magnetic resonance images are often acquired as several 2D slices and stacked into a 3D volume, yielding a lower through-plane resolution than in-plane resolution. Many super-resolution (SR) methods have been proposed to address this, incl…
View article: Nucleus subtype classification using inter-modality learning
Nucleus subtype classification using inter-modality learning Open
Understanding the way cells communicate, co-locate, and interrelate is essential to understanding human physiology. Hematoxylin and eosin (H&E) staining is ubiquitously available both for clinical studies and research. The Colon Nucleus Id…
View article: Self-supervised super-resolution of 2-D pre-clinical MRI acquisitions
Self-supervised super-resolution of 2-D pre-clinical MRI acquisitions Open
Animal models are pivotal in disease research and the advancement of therapeutic methods. The translation of results from these models to clinical applications is enhanced by employing technologies which are consistent for both humans and …
View article: Nucleus subtype classification using inter-modality learning
Nucleus subtype classification using inter-modality learning Open
Understanding the way cells communicate, co-locate, and interrelate is essential to understanding human physiology. Hematoxylin and eosin (H&E) staining is ubiquitously available both for clinical studies and research. The Colon Nucleus Id…
View article: Super-resolution multi-contrast unbiased eye atlases with deep probabilistic refinement
Super-resolution multi-contrast unbiased eye atlases with deep probabilistic refinement Open
Purpose: Eye morphology varies significantly across the population, especially for the orbit and optic nerve. These variations limit the feasibility and robustness of generalizing population-wise features of eye organs to an unbiased spati…
View article: AniRes2D: Anisotropic Residual-enhanced Diffusion for 2D MR Super-Resolution
AniRes2D: Anisotropic Residual-enhanced Diffusion for 2D MR Super-Resolution Open
Anisotropic low-resolution (LR) magnetic resonance (MR) images are fast to obtain but hinder automated processing. We propose to use denoising diffusion probabilistic models (DDPMs) to super-resolve these 2D-acquired LR MR slices. This pap…
View article: Towards an accurate and generalizable multiple sclerosis lesion segmentation model using self-ensembled lesion fusion
Towards an accurate and generalizable multiple sclerosis lesion segmentation model using self-ensembled lesion fusion Open
Automatic multiple sclerosis (MS) lesion segmentation using multi-contrast magnetic resonance (MR) images provides improved efficiency and reproducibility compared to manual delineation. Current state-of-the-art automatic MS lesion segment…
View article: Harmonization-enriched domain adaptation with light fine-tuning for multiple sclerosis lesion segmentation
Harmonization-enriched domain adaptation with light fine-tuning for multiple sclerosis lesion segmentation Open
Deep learning algorithms utilizing magnetic resonance (MR) images have demonstrated cutting-edge proficiency in autonomously segmenting multiple sclerosis (MS) lesions. Despite their achievements, these algorithms may struggle to extend th…
View article: HACA3: A unified approach for multi-site MR image harmonization
HACA3: A unified approach for multi-site MR image harmonization Open
View article: No ultrasounds detected from fungi when dehydrated
No ultrasounds detected from fungi when dehydrated Open
Many organisms (including certain plant species) can be observed to emit sounds, potentially signifying threat alerts. Sensitivity to such sounds and vibrations may also play an important role in the lives of fungi. In this work, we explor…
View article: Exploring shared memory architectures for end-to-end gigapixel deep learning
Exploring shared memory architectures for end-to-end gigapixel deep learning Open
Deep learning has made great strides in medical imaging, enabled by hardware advances in GPUs. One major constraint for the development of new models has been the saturation of GPU memory resources during training. This is especially true …
View article: A deep generative prior for high-resolution isotropic MR head slices
A deep generative prior for high-resolution isotropic MR head slices Open
Generative priors for magnetic resonance (MR) images have been used in a number of medical image analysis applications. Due to the plethora of deep learning methods based on 2D medical images, it would be beneficial to have a generator tra…
View article: Characteristics for Machine Learning Detection of Large Vessel Occlusion on Computed Tomography Angiography
Characteristics for Machine Learning Detection of Large Vessel Occlusion on Computed Tomography Angiography Open
Detection of large vessel occlusion (LVO) using machine learning on computed tomography angiography (CTA) may help stroke triage, yet applicability across varied patient and image characteristics has not been examined. The study will exami…
View article: Self-Supervised Super-Resolution for Anisotropic MR Images with and Without Slice Gap
Self-Supervised Super-Resolution for Anisotropic MR Images with and Without Slice Gap Open
View article: HACA3: A Unified Approach for Multi-site MR Image Harmonization
HACA3: A Unified Approach for Multi-site MR Image Harmonization Open
The lack of standardization is a prominent issue in magnetic resonance (MR) imaging. This often causes undesired contrast variations in the acquired images due to differences in hardware and acquisition parameters. In recent years, image s…
View article: Enlarged perivascular space burden associations with arterial stiffness and cognition
Enlarged perivascular space burden associations with arterial stiffness and cognition Open