Topic Name:
Disease Tracking Through Follow-Up Scans
DT2FS
Objectives
- To develop an accurate system for detecting and classifying brain tumors, specifically gliomas, from MRI/CT scans, addressing both initial diagnoses and progression.
- To enable longitudinal tracking of tumor changes over time to support timely and informed treatment decisions, aiding in early intervention if tumor progression is detected.
- Automated segmentation of liver segment on hepatic venous phase CT images using AI
- Comparative analysis of Breast-Tumor Bed Volumes in Breast Cancer Patients treated with Radiotherapy using Surgical Clips & AI based models.
- Predicting the shifts in Spinal cord in Head and Neck Cancer Patients receiving Radiotherapy.
- Bladder filling from initiation to completion of radiotherapy in women with cervical cancer using GANS
Issues Involved
- Manual Process of Data Collection and Expert Annotation
- Feature enhancement on Complex High Dimensional Data
- Achieving Clinical Standard of Precision
- Ensuring Process Agnostic Integration of Model Pipeline
- High Computational Requirements for Deep Learning Attention Based Models
Team Lead
Dr. Manoj Sankhe
manoj.sankhe@nmims.edu
Team Members
Dr. Prashasti Kanikar
prashasti.kanikar@nmims.edu
Dr. Prashant Kharote
prashant.kharote@nmims.edu
Dr. Sonal Parmar
Sonal.Parmar@nmims.edu
