Artificial Intelligence -based Computer Aided Early Diagnosis for low dose CT scans

Principal Investigator

Name
Jolu Ninan

Degrees
Masters Student

Institution
Abu Dhabi University

Position Title
Graduate Researcher

Email
jolujjn@gmail.com

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-450

Initial CDAS Request Approval
Nov 19, 2018

Title
Artificial Intelligence -based Computer Aided Early Diagnosis for low dose CT scans

Summary
The aim of this project is to develop an AI-based computer aided early detection system to help diagnose lung cancer at its early stages. A deep neural net approach will be adopted to classify benign and malignant nodules. Semantic Segmentation will also be used to label anatomy and pathological ROI.

Aims

- Lung Nodule feature recognition-based analysis.
- Classification model to classify benign and malignant lung nodules and management of false positives.
- Risk and survival rate prediction model for lung cancer for the subject in the future.
- Deep Learning approach using neural nets for semantic segmentation of the chest CT of the subject

Collaborators

Jolu Jose Ninan (1039789@students.adu.ac.ae)