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ORCIDNikhil Cherian Kurian
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2020 – today
- 2025
[c17]Akhila Krishna K, Nikhil Cherian Kurian, Abhijeet Patil, Amruta Parulekar, Pranav Jeevan, Amit Sethi:
Pathogen-X: A Cross-Modal Genomic Feature Trans-Align Network for Enhanced Survival Prediction from Histopathology Images. ISBI 2025: 1-4- 2024
- [c16]Pranav Jeevan, Nikhil Cherian Kurian, Amit Sethi:
Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers. BIOSTEC (1) 2024: 216-222 - [i9]Abhijeet Patil, Harsh Diwakar, Jay Sawant, Nikhil Cherian Kurian, Subhash Yadav, Swapnil Rane, Tripti Bameta, Amit Sethi:
Efficient Quality Control of Whole Slide Pathology Images with Human-in-the-loop Training. CoRR abs/2409.19587 (2024) - [i8]Akhila Krishna K, Nikhil Cherian Kurian, Abhijeet Patil, Amruta Parulekar
, Amit Sethi:
PathoGen-X: A Cross-Modal Genomic Feature Trans-Align Network for Enhanced Survival Prediction from Histopathology Images. CoRR abs/2411.00749 (2024) - 2023
- [c15]Nikhil Cherian Kurian, S. Varsha, Abhijit Patil, Shashikant Khade, Amit Sethi:
Robust Semi-Supervised Learning for Histopathology Images Through Self-Supervision Guided Out-of-Distribution Scoring. BIBE 2023: 121-128 - [c14]Tirupati Saketh Chandra, Sahar Almahfouz Nasser, Nikhil Cherian Kurian, Amit Sethi:
Improving Mitosis Detection via UNet-Based Adversarial Domain Homogenizer. BIOIMAGING 2023: 52-56 - [c13]Ravi Kant Gupta, Shivani Nandgaonkar, Nikhil Cherian Kurian, Tripti Bameta, Subhash Yadav, Rajiv Kumar Kaushal, Swapnil Rane, Amit Sethi:
EGFR Mutation Prediction of Lung Biopsy Images Using Deep Learning. BIOIMAGING 2023: 102-109 - [c12]Nikhil Cherian Kurian, Niraj Kumar:
Improved Multi-Step, Multi-Variate, and Spatiotemporal 5G Data Usage Forecasting Without Deploying Data Imputation Techniques. GLOBECOM 2023: 7417-7422 - [c11]Akhila Krishna K, Ravi Kant Gupta, Nikhil Cherian Kurian, Pranav Jeevan, Amit Sethi:
Heterogeneous Graphs Model Spatial Relationship Between Biological Entities for Breast Cancer Diagnosis. GRAIL/OCELOT@MICCAI 2023: 97-106 - [i7]Pranav Jeevan, Nikhil Cherian Kurian, Amit Sethi:
Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers. CoRR abs/2302.11488 (2023) - [i6]Nikhil Cherian Kurian, S. Varsha, Abhijit Patil, Shashikant Khade, Amit Sethi:
Robust Semi-Supervised Learning for Histopathology Images through Self-Supervision Guided Out-of-Distribution Scoring. CoRR abs/2303.09930 (2023) - [i5]Akhila Krishna K, Ravi Kant Gupta, Nikhil Cherian Kurian, Pranav Jeevan, Amit Sethi:
Heterogeneous graphs model spatial relationships between biological entities for breast cancer diagnosis. CoRR abs/2307.08132 (2023) - 2022
- [j3]Ruchika Verma, Neeraj Kumar, Abhijeet Patil, Nikhil Cherian Kurian, Swapnil Rane, Amit Sethi:
Author's Reply to "MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge". IEEE Trans. Medical Imaging 41(4): 1000-1003 (2022) - [c10]Nikhil Cherian Kurian, Amit Lehan, Gregory Verghese, Nimish Dharamshi, Swati Meena, Mengyuan Li, Fangfang Liu, Cheryl Gillet, Swapnil Rane, Anita Grigoriadis, Amit Sethi:
Deep Multi-Scale U-Net Architecture and Label-Noise Robust Training Strategies for Histopathological Image Segmentation. BIBE 2022: 91-96 - [c9]Sahar Almahfouz Nasser, Nikhil Cherian Kurian, Mohit Meena, Saqib Shamsi, Amit Sethi:
WSSAMNet: Weakly Supervised Semantic Attentive Medical Image Registration Network. BrainLes@MICCAI (2) 2022: 15-24 - [c8]Nikhil Cherian Kurian, S. Varsha, Akshay Bajpai, Sunil Patel, Amit Sethi:
Improved Histology Image Classification under Label Noise Via Feature Aggregating Memory Banks. ISBI 2022: 1-5 - [i4]Sahar Almahfouz Nasser, Nikhil Cherian Kurian, Saqib Shamsi, Mohit Meena, Amit Sethi:
WSSAMNet: Weakly Supervised Semantic Attentive Medical Image Registration Network. CoRR abs/2203.07114 (2022) - [i3]Nikhil Cherian Kurian, Amit Lohan, Gregory Verghese, Nimish Dharamshi, Swati Meena, Mengyuan Li, Fangfang Liu, Cheryl Gillet, Swapnil Rane, Anita Grigoriadis, Amit Sethi:
Deep Multi-Scale U-Net Architecture and Noise-Robust Training Strategies for Histopathological Image Segmentation. CoRR abs/2205.01777 (2022) - [i2]Tirupati Saketh Chandra, Sahar Almahfouz Nasser, Nikhil Cherian Kurian, Amit Sethi:
Improving Mitosis Detection Via UNet-based Adversarial Domain Homogenizer. CoRR abs/2209.09193 (2022) - 2021
- [j2]Ruchika Verma, Neeraj Kumar, Abhijeet Patil, Nikhil Cherian Kurian, Swapnil Rane, Simon Graham, Quoc Dang Vu, Mieke Zwager, Shan-E-Ahmed Raza, Nasir M. Rajpoot, Xiyi Wu, Huai Chen, Yijie Huang, Lisheng Wang, Hyun Jung, G. Thomas Brown, Yanling Liu, Shuolin Liu, Seyed Alireza Fatemi Jahromi, Ali Asghar Khani, Ehsan Montahaei, Mahdieh Soleymani Baghshah, Hamid Behroozi, Pavel Semkin, Alexandr Rassadin, Prasad Dutande, Romil Lodaya, Ujjwal Baid, Bhakti Baheti, Sanjay N. Talbar, Amirreza Mahbod, Rupert Ecker, Isabella Ellinger, Zhipeng Luo, Bin Dong, Zhengyu Xu, Yuehan Yao, Shuai Lv, Ming Feng, Kele Xu, Hasib Zunair, Abdessamad Ben Hamza, Steven M. Smiley, Tang-Kai Yin, Qi-Rui Fang, Shikhar Srivastava, Dwarikanath Mahapatra, Lubomira Trnavska, Hanyun Zhang, Priya Lakshmi Narayanan, Justin Law, Yinyin Yuan, Abhiroop Tejomay, Aditya Mitkari, Dinesh Koka, Vikas Ramachandra, Lata Kini, Amit Sethi:
MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge. IEEE Trans. Medical Imaging 40(12): 3413-3423 (2021) - [j1]Nikhil Cherian Kurian, Amit Sethi, Anil Reddy Konduru, Abhishek Mahajan, Swapnil Ulhas Rane:
A 2021 update on cancer image analytics with deep learning. WIREs Data Mining Knowl. Discov. 11(4) (2021) - [c7]Nikhil Cherian Kurian, Gurparkash Singh, Poorvi Hebbar, Shreekanya Kodate, Swapnil Rane, Amit Sethi:
Robust Classification of Histology Images Exploiting Adversarial Auto Encoders. EMBC 2021: 2871-2874 - [c6]Abhijeet Patil, Mohd. Talha, Aniket Bhatia, Nikhil Cherian Kurian, Sammed Mangale, Sunil Patel, Amit Sethi:
Fast, Self Supervised, Fully Convolutional Color Normalization Of H&E Stained Images. ISBI 2021: 1563-1567 - [c5]Nikhil Cherian Kurian, Pragati Shuddhodhan Meshram, Abhijeet Patil, Sunil Patel, Amit Sethi:
Sample Specific Generalized Cross Entropy for Robust Histology Image Classification. ISBI 2021: 1934-1938 - [c4]Sahar Almahfouz Nasser, Nikhil Cherian Kurian, Amit Sethi:
Domain Generalisation for Mitosis Detection Exploting Preprocessing Homogenizers. MIDOG/MOOD/Learn2Reg@MICCAI 2021: 77-80 - 2020
- [c3]Bibin Wilson, Nikhil Cherian Kurian, Anand Singh, Amit Sethi:
Satellite-Derived Bathymetry Using Deep Convolutional Neural Network. IGARSS 2020: 2280-2283 - [i1]Abhijeet Patil, Mohd. Talha, Aniket Bhatia, Nikhil Cherian Kurian, Sammed Mangale, Sunil Patel, Amit Sethi:
Fast, Self Supervised, Fully Convolutional Color Normalization of H&E Stained Images. CoRR abs/2011.15000 (2020)
2010 – 2019
- 2019
- [c2]Viraf Patrawala, Nikhil Cherian Kurian, Amit Sethi:
Improving Histopathology Classification using Learnable Preprocessing. TENCON 2019: 2460-2465 - 2016
- [c1]Kashyap Patel, Nikhil Cherian Kurian, Nithin V. George:
Time frequency analysis: A sparse S transform approach. ISPACS 2016: 1-4
Coauthor Index
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