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2020 – today
- 2024
[c6]Ardhendu Sekhar
, Vrinda Goel, Garima Jain, Abhijeet Patil, Ravi Kant Gupta, Tripti Bameta, Swapnil Rane, Amit Sethi:
HER2 and Fish Status Prediction in Breast Biopsy H&E-Stained Images Using Deep Learning. BIBE 2024: 1-8- [c5]Amruta Parulekar, Utkarsh Kanwat, Ravi Kant Gupta, Medha Chippa, Thomas Jacob, Tripti Bameta, Swapnil Rane, Amit Sethi:
Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification. BIOSTEC (1) 2024: 281-288 - [i4]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) - [i3]Abhijeet Patil, Garima Jain, Harsh Diwakar, Jay Sawant, Tripti Bameta, Swapnil Rane, Amit Sethi:
Semantic Segmentation Based Quality Control of Histopathology Whole Slide Images. CoRR abs/2410.03289 (2024) - 2023
- [c4]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 - [i2]Amruta Parulekar, Utkarsh Kanwat, Ravi Kant Gupta, Medha Chippa, Thomas Jacob, Tripti Bameta, Swapnil Rane, Amit Sethi:
Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification. CoRR abs/2310.03346 (2023) - 2022
- [j5]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) - [c3]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 - [i1]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) - 2021
- [j4]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) - [j3]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) - [c2]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 - 2020
- [j2]Ujjwal Baid, Sanjay N. Talbar, Swapnil Rane, Sudeep Gupta, Meenakshi H. Thakur, Aliasgar Moiyadi, Nilesh Sable, Mayuresh Akolkar, Abhishek Mahajan:
A Novel Approach for Fully Automatic Intra-Tumor Segmentation With 3D U-Net Architecture for Gliomas. Frontiers Comput. Neurosci. 14: 10 (2020) - [j1]Ujjwal Baid, Swapnil Rane, Sanjay N. Talbar, Sudeep Gupta, Meenakshi H. Thakur, Aliasgar Moiyadi, Abhishek Mahajan:
Overall Survival Prediction in Glioblastoma With Radiomic Features Using Machine Learning. Frontiers Comput. Neurosci. 14: 61 (2020)
2010 – 2019
- 2018
- [c1]Ujjwal Baid, Sanjay N. Talbar, Swapnil Rane, Sudeep Gupta, Meenakshi H. Thakur, Aliasgar Moiyadi, Siddhesh Thakur, Abhishek Mahajan:
Deep Learning Radiomics Algorithm for Gliomas (DRAG) Model: A Novel Approach Using 3D UNET Based Deep Convolutional Neural Network for Predicting Survival in Gliomas. BrainLes@MICCAI (2) 2018: 369-379
Coauthor Index
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