most citedVisual attention analysis of pathologists examining whole slide images of Prostate cancer

5 citations · 5 across the 3 of their papers we have counts for

collaborators

5 papers

q-bio.QM2022

A Novel Framework for Characterization of Tumor-Immune Spatial Relationships in Tumor Microenvironment

Mahmudul Hasan, Jakub R. Kaczmarzyk, David Paredes +9

Understanding the impact of tumor biology on the composition of nearby cells often requires characterizing the impact of biologically distinct tumor regions. Biomarkers have been d…

eess.IV20225 cited

Visual attention analysis of pathologists examining whole slide images of Prostate cancer

Souradeep Chakraborty, Ke Ma, Rajarsi Gupta +4

We study the attention of pathologists as they examine whole-slide images (WSIs) of prostate cancer tissue using a digital microscope. To the best of our knowledge, our study is th…

cs.LG2020

Identifying Risk of Opioid Use Disorder for Patients Taking Opioid Medications with Deep Learning

Xinyu Dong, Jianyuan Deng, Sina Rashidian +6

The United States is experiencing an opioid epidemic, and there were more than 10 million opioid misusers aged 12 or older each year. Identifying patients at high risk of Opioid Us…

cs.GR2020

Representing Whole Slide Cancer Image Features with Hilbert Curves

Erich Bremer, Jonas Almeida, Joel Saltz

Regions of Interest (ROI) contain morphological features in pathology whole slide images (WSI) are delimited with polygons[1]. These polygons are often represented in either a text…

eess.IV2020

Dataset of Segmented Nuclei in Hematoxylin and Eosin Stained Histopathology Images of 10 Cancer Types

Le Hou, Rajarsi Gupta, John S. Van Arnam +5

The distribution and appearance of nuclei are essential markers for the diagnosis and study of cancer. Despite the importance of nuclear morphology, there is a lack of large scale,…