55 citations · 285 across the 36 of their papers we have counts for
37 papers
Voronoi-Markov chain and spatial entropy for point pattern analysis
James C. Mathews, Francisco Couzo, Aleksandr Petrov +2
In this paper, we revisit the concept of entropy in the spatial context with the aim of deriving computable and interpretable metrics for point pattern analysis in domains such as…
ImPartial: Multi-channel Whole-Cell Segmentation using Partial Annotations
Gunjan Shrivastava, Saad Nadeem
Accurate cell segmentation in pathology images typically requires dense pixel-wise annotations, which are costly and time-consuming to obtain. This challenge is especially importan…
Rethinking Histology Slide Digitization Workflows for Low-Resource Settings
Talat Zehra, Joseph Marino, Wendy Wang +2
Histology slide digitization is becoming essential for telepathology (remote consultation), knowledge sharing (education), and using the state-of-the-art artificial intelligence al…
RT-GAN: Recurrent Temporal GAN for Adding Lightweight Temporal Consistency to Frame-Based Domain Translation Approaches
Shawn Mathew, Saad Nadeem, Alvin C. Goh +1
Fourteen million colonoscopies are performed annually just in the U.S. However, the videos from these colonoscopies are not saved due to storage constraints (each video from a high…
An AI-Ready Multiplex Staining Dataset for Reproducible and Accurate Characterization of Tumor Immune Microenvironment
Parmida Ghahremani, Joseph Marino, Juan Hernandez-Prera +4
We introduce a new AI-ready computational pathology dataset containing restained and co-registered digitized images from eight head-and-neck squamous cell carcinoma patients. Speci…
RMSim: Controlled Respiratory Motion Simulation on Static Patient Scans
Donghoon Lee, Ellen Yorke, Masoud Zarepisheh +2
This work aims to generate realistic anatomical deformations from static patient scans. Specifically, we present a method to generate these deformations/augmentations via deep lear…
Stain-invariant self supervised learning for histopathology image analysis
Alexandre Tiard, Alex Wong, David Joon Ho +5
We present a self-supervised algorithm for several classification tasks within hematoxylin and eosin (H&E) stained images of breast cancer. Our method is robust to stain variations…
Domain Knowledge Driven 3D Dose Prediction Using Moment-Based Loss Function
Gourav Jhanwar, Navdeep Dahiya, Parmida Ghahremani +2
Dose volume histogram (DVH) metrics are widely accepted evaluation criteria in the clinic. However, incorporating these metrics into deep learning dose prediction models is challen…
CLTS-GAN: Color-Lighting-Texture-Specular Reflection Augmentation for Colonoscopy
Shawn Mathew, Saad Nadeem, Arie Kaufman
Automated analysis of optical colonoscopy (OC) video frames (to assist endoscopists during OC) is challenging due to variations in color, lighting, texture, and specular reflection…
CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Radiomics and malignancy prediction
Wookjin Choi, Navdeep Dahiya, Saad Nadeem
Spiculations/lobulations, sharp/curved spikes on the surface of lung nodules, are good predictors of lung cancer malignancy and hence, are routinely assessed and reported by radiol…
DeepLIIF: An Online Platform for Quantification of Clinical Pathology Slides
Parmida Ghahremani, Joseph Marino, Ricardo Dodds +1
In the clinic, resected tissue samples are stained with Hematoxylin-and-Eosin (H&E) and/or Immunhistochemistry (IHC) stains and presented to the pathologists on glass slides or as…
An exact test for significance of clusters in binary data
James Mathews, Cameron Crowe, Rami Vanguri +3
Unsupervised clustering of feature matrix data is an indispensible technique for exploratory data analysis and quality control of experimental data. However, clusters are difficult…
Deep Learning 3D Dose Prediction for Conventional Lung IMRT Using Consistent/Unbiased Automated Plans
Navdeep Dahiya, Gourav Jhanwar, Anthony Yezzi +2
Deep learning (DL) 3D dose prediction has recently gained a lot of attention. However, the variability of plan quality in the training dataset, generated manually by planners with…
FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos
Shawn Mathew, Saad Nadeem, Arie Kaufman
Haustral folds are colon wall protrusions implicated for high polyp miss rate during optical colonoscopy procedures. If segmented accurately, haustral folds can allow for better es…
Deformation Driven Seq2Seq Longitudinal Tumor and Organs-at-Risk Prediction for Radiotherapy
Donghoon Lee, Sadegh R Alam, Jue Jiang +3
Purpose: Radiotherapy presents unique challenges and clinical requirements for longitudinal tumor and organ-at-risk (OAR) prediction during treatment. The challenges include tumor…
Multitask 3D CBCT-to-CT Translation and Organs-at-Risk Segmentation Using Physics-Based Data Augmentation
Navdeep Dahiya, Sadegh R Alam, Pengpeng Zhang +3
In current clinical practice, noisy and artifact-ridden weekly cone-beam computed tomography (CBCT) images are only used for patient setup during radiotherapy. Treatment planning i…
Visualizing Missing Surfaces In Colonoscopy Videos using Shared Latent Space Representations
Shawn Mathew, Saad Nadeem, Arie Kaufman
Optical colonoscopy (OC), the most prevalent colon cancer screening tool, has a high miss rate due to a number of factors, including the geometry of the colon (haustral fold and sh…
Multimarginal Wasserstein Barycenter for Stain Normalization and Augmentation
Saad Nadeem, Travis Hollmann, Allen Tannenbaum
Variations in hematoxylin and eosin (H&E) stained images (due to clinical lab protocols, scanners, etc) directly impact the quality and accuracy of clinical diagnosis, and hence it…
Generalizable Cone Beam CT Esophagus Segmentation Using Physics-Based Data Augmentation
Sadegh R Alam, Tianfang Li, Pengpeng Zhang +2
Automated segmentation of esophagus is critical in image guided/adaptive radiotherapy of lung cancer to minimize radiation-induced toxicities such as acute esophagitis. We develope…
Augmenting Colonoscopy using Extended and Directional CycleGAN for Lossy Image Translation
Shawn Mathew, Saad Nadeem, Sruti Kumari +1
Colorectal cancer screening modalities, such as optical colonoscopy (OC) and virtual colonoscopy (VC), are critical for diagnosing and ultimately removing polyps (precursors of col…
Fisher-Rao Regularized Transport Analysis of the Glymphatic System and Waste Drainage
Rena Elkin, Saad Nadeem, Hedok Lee +2
In this work, a unified representation of all the time-varying dynamics is accomplished with a Lagrangian framework for analyzing Fisher-Rao regularized dynamical optimal mass tran…
LMap: Shape-Preserving Local Mappings for Biomedical Visualization
Saad Nadeem, Xianfeng Gu, Arie Kaufman
Visualization of medical organs and biological structures is a challenging task because of their complex geometry and the resultant occlusions. Global spherical and planar mapping…
Spherical Parameterization Balancing Angle and Area Distortions
Saad Nadeem, Zhengyu Su, Wei Zeng +2
This work presents a novel framework for spherical mesh parameterization. An efficient angle-preserving spherical parameterization algorithm is introduced, which is based on dynami…
C2A: Crowd Consensus Analytics for Virtual Colonoscopy
Ji Hwan Park, Saad Nadeem, Seyedkoosha Mirhosseini +1
We present a medical crowdsourcing visual analytics platform called C{}A to visualize, classify and filter crowdsourced clinical data. More specifically, CA is used to buil…