Mahendra Khened

Medicine · Health Sciences

12h-index3.9kcitations21works0.02yr avg
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Research Topics

Radiomics and Machine Learning in Medical Imaging(12), Advanced Neural Network Applications(10), Brain Tumor Detection and Classification(10), AI in cancer detection(9), Medical Image Segmentation Techniques(2)

Publications21 total

Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches
UNC Libraries·2025Open Access
The Liver Tumor Segmentation Benchmark (LiTS)
Medical Image Analysis·2022· 1.0k citedOpen Access
A generalized deep learning framework for whole-slide image segmentation and analysis
Scientific Reports·2021· 7 citedOpen Access
Brain Tumor Segmentation and Survival Prediction using Automatic Hard\n mining in 3D CNN Architecture
arXiv (Cornell University)·2021Open Access
Brain Tumor Segmentation and Survival Prediction Using Automatic Hard Mining in 3D CNN Architecture
Lecture notes in computer science·2021· 5 citedOpen Access
PAIP 2019: Liver cancer segmentation challenge
Medical Image Analysis·2020· 109 citedOpen Access
Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches
Frontiers in Neuroscience·2020· 95 citedOpen Access
A Generalized Deep Learning Framework for Whole-Slide Image Segmentation\n and Analysis
arXiv (Cornell University)·2020Open Access
NTIRE 2019 Challenge on Image Enhancement: Methods and Results
2019· 45 cited
Medical image retrieval using Resnet-18 for clinical diagnosis
2019· 28 cited
3D convolution neural networks for molecular subtype prediction in glioblastoma multiforme
2019· 5 cited
The Liver Tumor Segmentation Benchmark (LiTS)
Rare & Special e-Zone (The Hong Kong University of Science and Technology)·2019· 251 citedOpen Access
Ensemble of Fully Convolutional Neural Network for Brain Tumor Segmentation from Magnetic Resonance Images
Lecture notes in computer science·2019· 20 cited
Fully Automatic Segmentation for Ischemic Stroke Using CT Perfusion Maps
Lecture notes in computer science·2019· 9 cited
A Combined Radio-Histological Approach for Classification of Low Grade Gliomas
Lecture notes in computer science·2019· 12 cited
Convolutional Neural Network for Kidney and kidney Tumor segmentation
2019· 3 citedOpen Access
Fully convolutional multi-scale residual DenseNets for cardiac segmentation and automated cardiac diagnosis using ensemble of classifiers
Medical Image Analysis·2018· 19 citedOpen Access
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
IEEE Transactions on Medical Imaging·2018· 2.1k citedOpen Access
Fully Convolutional Multi-scale Residual DenseNets for Cardiac\n Segmentation and Automated Cardiac Diagnosis using Ensemble of Classifiers
arXiv (Cornell University)·2018Open Access
2D-Densely Connected Convolution Neural Networks for automatic Liver and Tumor Segmentation
arXiv (Cornell University)·2018· 68 citedOpen Access
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Frequent Co-authors

Ganapathy Krishnamurthi(21), Avinash Kori(11), Vikas Kumar Anand(6), Pheng‐Ann Heng(4), Spyridon Bakas(4), Varghese Alex(4), Varghese Alex Kollerathu(3), Fabian Isensee(3), Paul F. Jäger(3), Klaus Maier‐Hein(3), Krishna Chaitanya Kaluva(3), Haran Rajkumar(3), Aditya Bagari(3), Ashish Kumar(3), Pranav Aurangabadkar(3), Patrick Bilic(2), Patrick Ferdinand Christ(2), Hongwei Li(2), Eugene Vorontsov(2), Georgios Kaissis(2)