Lung Nodule Risk Prediction



About:

Aim of this group is to design a software tool that will predict the risky lung nodules from CT and X-ray images to detect this disease at an early stage. Hence the survival rate of this disease can increase. This is a collaborative research among University of Calcutta, Peerless Hospital and University of Nebraska Lincoln, United States of America, involving three technologist and two doctors in this project.
Ms. Jhilam Mukherjee
PhD Scholar
A.K.C.S.I.T
University of Calcutta
Jhilam.mukherjee20@gmail.com






Dr. Amlan Chakrabarti
Professor (PhD Supervisor)
A.K.C.S.I.T
University of Calcutta
achakra12@yahoo.com






Dr. Madhuchanda Kar
PhD Supervisor
Clinical Director
Department of Oncology
Peerless Hospital Kolkata
madhuchandakar@yahoo.com






Dr. Sruti Das Choudhury
Collaborator
Department of Computer Science and Engineering
University of Nebraska-Lincoin
United States of America
srutidc@gmail.com







Dr. Sayan Das
Collaborator
Dept of Radiology & Imaging & Interventional Radiology
Peerless Hospital, Kolkata
drnayas@gmail.com










Publications:

  1. Jhilam Mukherjee, Amlan Chakrabarti, Soharab Hossain Shaikh, Madhuchanda Kar, Automatic Detection and Classification of Solitary Pulmonary Nodules from Lung CT Images, Fourth International Conference of Emerging Applications of Information Technology (EAIT),2014.

  2. Jhilam Mukherjee, Soharab Hossain Shaikh, Madhuchanda Kar, Amlan Chakrabarti, A Comparative Analysis of Image Segmentation Techniques Toward Automatic Risk Prediction of Solitary Pulmonary Nodules, Advanced Computing and Systems for Security ,Springer LNCS,2016.

  3. Jhilam Mukherjee, Bishwadeep Sikder, Soham Majumdar, Amlan Chakrabarti, Madhuchanda Kar, Sayan Das, A Novel Technique for Contrast Enhancement of Chest X-ray Images Based on Bio-Inspired Meta-heuristics, Accepted in Advanced Computing and Systems for Security



Collaborations: