55 citations · 285 across the 36 of their papers we have counts for
20 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
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…
Visualization Framework for Colonoscopy Videos
Saad Nadeem, Arie Kaufman
We present a visualization framework for annotating and comparing colonoscopy videos, where these annotations can then be used for semi-automatic report generation at the end of th…
Corresponding Supine and Prone Colon Visualization Using Eigenfunction Analysis and Fold Modeling
Saad Nadeem, Joseph Marino, Xianfeng Gu +1
We present a method for registration and visualization of corresponding supine and prone virtual colonoscopy scans based on eigenfunction analysis and fold modeling. In virtual col…
FeatureLego: Volume Exploration Using Exhaustive Clustering of Super-Voxels
Shreeraj Jadhav, Saad Nadeem, Arie Kaufman
We present a volume exploration framework, FeatureLego, that uses a novel voxel clustering approach for efficient selection of semantic features. We partition the input volume into…
Radiative Transport Based Flame Volume Reconstruction from Videos
Liang Shen, Dengming Zhu, Saad Nadeem +2
We introduce a novel approach for flame volume reconstruction from videos using inexpensive charge-coupled device (CCD) consumer cameras. The approach includes an economical data c…
Crowd-Assisted Polyp Annotation of Virtual Colonoscopy Videos
Ji Hwan Park, Saad Nadeem, Joseph Marino +3
Virtual colonoscopy (VC) allows a radiologist to navigate through a 3D colon model reconstructed from a computed tomography scan of the abdomen, looking for polyps, the precursors…
Crowdsourcing Lung Nodules Detection and Annotation
Saeed Boorboor, Saad Nadeem, Ji Hwan Park +2
We present crowdsourcing as an additional modality to aid radiologists in the diagnosis of lung cancer from clinical chest computed tomography (CT) scans. More specifically, a comp…
GlymphVIS: Visualizing Glymphatic Transport Pathways Using Regularized Optimal Transport
Rena Elkin, Saad Nadeem, Eldad Haber +4
The glymphatic system (GS) is a transit passage that facilitates brain metabolic waste removal and its dysfunction has been associated with neurodegenerative diseases such as Alzhe…
Quantification of Local Metabolic Tumor Volume Changes by Registering Blended PET-CT Images for Prediction of Pathologic Tumor Response
Sadegh Riyahi, Wookjin Choi, Chia-Ju Liu +8
Quantification of local metabolic tumor volume (MTV) chan-ges after Chemo-radiotherapy would allow accurate tumor response evaluation. Currently, local MTV changes in esophageal (s…
Reproducible and Interpretable Spiculation Quantification for Lung Cancer Screening
Wookjin Choi, Saad Nadeem, Sadegh Riyahi +3
Spiculations are important predictors of lung cancer malignancy, which are spikes on the surface of the pulmonary nodules. In this study, we proposed an interpretable and parameter…
Depth Reconstruction and Computer-Aided Polyp Detection in Optical Colonoscopy Video Frames
Saad Nadeem, Arie Kaufman
We present a computer-aided detection algorithm for polyps in optical colonoscopy images. Polyps are the precursors to colon cancer. In the US alone, more than 14 million optical c…