Search Results for author: Satyananda Kashyap

Found 15 papers, 3 papers with code

Basis Scaling and Double Pruning for Efficient Transfer Learning

no code implementations6 Aug 2021 Ken C. L. Wong, Satyananda Kashyap, Mehdi Moradi

Using singular value decomposition, we decompose a convolutional layer into two layers: a convolutional layer with the orthonormal basis vectors as the filters, and a layer that we name "BasisScalingConv", which is responsible for rescaling the features and transforming them back to the original space.

Network Pruning Transfer Learning

Chest ImaGenome Dataset for Clinical Reasoning

1 code implementation31 Jul 2021 Joy T. Wu, Nkechinyere N. Agu, Ismini Lourentzou, Arjun Sharma, Joseph A. Paguio, Jasper S. Yao, Edward C. Dee, William Mitchell, Satyananda Kashyap, Andrea Giovannini, Leo A. Celi, Mehdi Moradi

Despite the progress in automatic detection of radiologic findings from chest X-ray (CXR) images in recent years, a quantitative evaluation of the explainability of these models is hampered by the lack of locally labeled datasets for different findings.

Computer Vision Natural Language Processing

Channel Scaling: A Scale-and-Select Approach for Transfer Learning

no code implementations22 Mar 2021 Ken C. L. Wong, Satyananda Kashyap, Mehdi Moradi

By imposing L1 regularization and thresholding on the scaling weights, this framework iteratively removes unnecessary feature channels from a pre-trained model.

Transfer Learning

Learning Invariant Feature Representation to Improve Generalization across Chest X-ray Datasets

no code implementations4 Aug 2020 Sandesh Ghimire, Satyananda Kashyap, Joy T. Wu, Alexandros Karargyris, Mehdi Moradi

Through pneumonia-classification experiments on multi-source chest X-ray datasets, we show that this algorithm helps in improving classification accuracy on a new source of X-ray dataset.

Chest X-ray Report Generation through Fine-Grained Label Learning

no code implementations27 Jul 2020 Tanveer Syeda-Mahmood, Ken C. L. Wong, Yaniv Gur, Joy T. Wu, Ashutosh Jadhav, Satyananda Kashyap, Alexandros Karargyris, Anup Pillai, Arjun Sharma, Ali Bin Syed, Orest Boyko, Mehdi Moradi

Obtaining automated preliminary read reports for common exams such as chest X-rays will expedite clinical workflows and improve operational efficiencies in hospitals.

Self-Training with Improved Regularization for Sample-Efficient Chest X-Ray Classification

no code implementations3 May 2020 Deepta Rajan, Jayaraman J. Thiagarajan, Alexandros Karargyris, Satyananda Kashyap

Automated diagnostic assistants in healthcare necessitate accurate AI models that can be trained with limited labeled data, can cope with severe class imbalances and can support simultaneous prediction of multiple disease conditions.

Data Augmentation Few-Shot Learning +1

Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation

no code implementations26 Jul 2019 Jayaraman J. Thiagarajan, Satyananda Kashyap, Alexandros Karagyris

Weakly supervised instance labeling using only image-level labels, in lieu of expensive fine-grained pixel annotations, is crucial in several applications including medical image analysis.

Breast Cancer Detection Computer Vision +4

Just-Enough Interaction Approach to Knee MRI Segmentation: Data from the Osteoarthritis Initiative

no code implementations10 Mar 2019 Satyananda Kashyap, Honghai Zhang, Milan Sonka

State-of-the-art automated segmentation algorithms are not 100\% accurate especially when segmenting difficult to interpret datasets like those with severe osteoarthritis (OA).

MRI segmentation

Learning-Based Cost Functions for 3D and 4D Multi-Surface Multi-Object Segmentation of Knee MRI: Data from the Osteoarthritis Initiative

no code implementations10 Mar 2019 Satyananda Kashyap, Honghai Zhang, Karan Rao, Milan Sonka

4D LOGISMOS validation on 108 MRIs from baseline and 12 month follow-up scans of 54 patients showed a significant reduction in segmentation errors (\emph{p}$<$0. 01) compared to 3D.

MRI segmentation Semantic Segmentation

Age prediction using a large chest X-ray dataset

no code implementations9 Mar 2019 Alexandros Karargyris, Satyananda Kashyap, Joy T. Wu, Arjun Sharma, Mehdi Moradi, Tanveer Syeda-Mahmood

Age prediction based on appearances of different anatomies in medical images has been clinically explored for many decades.

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