Deep Learning Models for Automated Diagnosis of Lung X-Ray CT Images

Deep Learning models for automated diagnosis of lung X-ray CT images

Objective

• The objective is to deploy deep learning models that automate medical image analysis and make it available to the medical imaging community at large., This project would involve the development of deep learning models for analyzing medical images specifically, the analysis of X-ray CT images for lung cancer diagnosis.

Description

• Radiologic analysis of lung CT volumes involves lesion segmentation followed by classification in to benign and malignant lesions. Malignant lesions can be classified into various lung cancer types., However, this can be a time consuming process and a bottleneck in case of large studies or pandemics where a large patient's population undergo scanning to rule out certain diseases., The projects goal is to develop automated analysis of lung X-ray CT volumes using deep learning models that will assist the radiologist to expedite the diagnosis.

Impact

• The developed models would be made available to clinicians on the cloud, free of cost, for an extended period., Then these models could be used for automating diagnosis in clinical centers that will attract large patient populations.