activity
20202025
most citedDeep Learning based NAS Score and Fibrosis Stage Prediction from CT and Pathology Data

1 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Evaluating the Suitability of Different Intraoral Scan Resolutions for Deep Learning-Based Tooth Segmentation

Daron Weekley, Jace Duckworth, Anastasiia Sukhanova +1

Intraoral scans are widely used in digital dentistry for tasks such as dental restoration, treatment planning, and orthodontic procedures. These scans contain detailed topological…

cs.CV20221 cited

Automatic Tooth Segmentation from 3D Dental Model using Deep Learning: A Quantitative Analysis of what can be learnt from a Single 3D Dental Model

Ananya Jana, Hrebesh Molly Subhash, Dimitris Metaxas

3D tooth segmentation is an important task for digital orthodontics. Several Deep Learning methods have been proposed for automatic tooth segmentation from 3D dental models or intr…

cs.LG2021

Global and Local Interpretation of black-box Machine Learning models to determine prognostic factors from early COVID-19 data

Ananya Jana, Carlos D. Minacapelli, Vinod Rustgi +1

The COVID-19 corona virus has claimed 4.1 million lives, as of July 24, 2021. A variety of machine learning models have been applied to related data to predict important factors su…

eess.IV2021

Liver Fibrosis and NAS scoring from CT images using self-supervised learning and texture encoding

Ananya Jana, Hui Qu, Carlos D. Minacapelli +3

Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver diseases (CLD) which can progress to liver cancer. The severity and treatment of NAFLD i…

eess.IV20201 cited

Deep Learning based NAS Score and Fibrosis Stage Prediction from CT and Pathology Data

Ananya Jana, Hui Qu, Puru Rattan +3

Non-Alcoholic Fatty Liver Disease (NAFLD) is becoming increasingly prevalent in the world population. Without diagnosis at the right time, NAFLD can lead to non-alcoholic steatohep…