most citedA Two-Stage Multiple Instance Learning Framework for the Detection of Breast Cancer in Mammograms

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

eess.IV2020

Lung Segmentation and Nodule Detection in Computed Tomography Scan using a Convolutional Neural Network Trained Adversarially using Turing Test Loss

Rakshith Sathish, Rachana Sathish, Ramanathan Sethuraman +1

Lung cancer is the most common form of cancer found worldwide with a high mortality rate. Early detection of pulmonary nodules by screening with a low-dose computed tomography (CT)…

cs.CV20202 cited

A Two-Stage Multiple Instance Learning Framework for the Detection of Breast Cancer in Mammograms

Sarath Chandra K, Arunava Chakravarty, Nirmalya Ghosh +3

Mammograms are commonly employed in the large scale screening of breast cancer which is primarily characterized by the presence of malignant masses. However, automated image-level…

cs.CV2020

Learning Decision Ensemble using a Graph Neural Network for Comorbidity Aware Chest Radiograph Screening

Arunava Chakravarty, Tandra Sarkar, Nirmalya Ghosh +2

Chest radiographs are primarily employed for the screening of cardio, thoracic and pulmonary conditions. Machine learning based automated solutions are being developed to reduce th…

cs.CV2020

A Systematic Search over Deep Convolutional Neural Network Architectures for Screening Chest Radiographs

Arka Mitra, Arunava Chakravarty, Nirmalya Ghosh +3

Chest radiographs are primarily employed for the screening of pulmonary and cardio-/thoracic conditions. Being undertaken at primary healthcare centers, they require the presence o…

cs.CV2018

Fully Convolutional Model for Variable Bit Length and Lossy High Density Compression of Mammograms

Aupendu Kar, Sri Phani Krishna Karri, Nirmalya Ghosh +2

Early works on medical image compression date to the 1980's with the impetus on deployment of teleradiology systems for high-resolution digital X-ray detectors. Commercially deploy…