Navchetan Awasthi

According to our database, Navchetan Awasthi authored at least 10 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

The MAMA-MIA Challenge: Advancing Generalizability and Fairness in Breast MRI Tumor Segmentation and Treatment Response Prediction.

Lidia Garrucho, Smriti Joshi, Kaisar Kushibar, Richard Osuala, Maciej Bobowicz, Xavier Bargalló, Paulius Jarusevicius, Kai Geissler, Raphael Schäfer, Muhammad Alberb, Tony Xu, Anne L. Martel, Daniel Sleiman, Navchetan Awasthi, Hadeel Awwad, Joan C. Vilanova, Robert Martí, Daan Schouten, Jeong Hoon Lee, Mirabela Rusu, Eleonora Poeta, Luisa Vargas, Eliana Pastor, Maria A. Zuluaga, Jessica Kächele, Dimitrios Bounias, Alexandra Ertl, Katarzyna Gwozdziewicz, Maria-Laura Cosaka, Pasant M. Abo-Elhoda, Sara W. Tantawy, Shorouq S. Sakrana, Norhan O. Shawky-Abdelfatah, Amr Muhammad Abdo-Salem, Androniki Kozana, Eugen Divjak, Gordana Ivanac, Katerina Nikiforaki, Michail E. Klontzas, Rosa García-Dosdá, Meltem Gulsun-Akpinar, Oguz Lafci, Carlos Martín-Isla, Oliver Díaz, Laura Igual, Karim Lekadir

CoRR, March, 2026

2025

Tumor Detection, Segmentation and Classification Challenge on Automated 3D Breast Ultrasound: The TDSC-ABUS Challenge.

Gongning Luo, Mingwang Xu, Hongyu Chen, Xinjie Liang, Xing Tao, Dong Ni, Hyunsu Jeong, Chulhong Kim, Raphael Stock, Michael Baumgartner, Yannick Kirchhoff, Maximilian Rokuss, Klaus H. Maier-Hein, Zhikai Yang, Tianyu Fan, Nicolas Boutry, Dmitry Tereshchenko, Arthur Moine, Maximilien Charmetant, Jan Sauer, Hao Du, Xiang-Hui Bai, Vipul Pai Raikar, Ricardo Montoya-del-Angel, Robert Marti, Miguel Luna, Dongmin Lee, Abdul Qayyum, Moona Mazher, Qihui Guo, Changyan Wang, Navchetan Awasthi, Qiaochu Zhao, Wei Wang, Kuanquan Wang, Qiucheng Wang, Suyu Dong

CoRR, January, 2025

Minimal data poisoning attack in federated learning for medical image classification: An attacker perspective.

K. Naveen Kumar, C. Krishna Mohan, Linga Reddy Cenkeramaddi, Navchetan Awasthi

Artif. Intell. Medicine, 2025

nnRAG - Incorporating Human-Feedback for Neural Network Driven Similarity Search: A Preliminary Feasibility Study.

Siva Singireddi, Sarthak Pandey, Rohit Pardasani, Raj Kiran V, Navchetan Awasthi

Proceedings of the 13th IEEE International Conference on Healthcare Informatics, 2025

2024

Demystifying the Effect of Receptive Field Size in U-Net Models for Medical Image Segmentation.

Vincent Loos, Rohit Pardasani, Navchetan Awasthi

CoRR, 2024

2021

Advanced Ultrasound and Photoacoustic Imaging in Cardiology.

Min Wu, Navchetan Awasthi, Nastaran Mohammadian Rad, Josien P. W. Pluim, Richard G. P. Lopata

Sensors, 2021

2020

Machine Learning and Deep Learning Approaches to Quantify Respiratory Distress Severity and Predict Critical Alarms.

Rohit Pardasani, Rupanjali Chaudhuri, Navchetan Awasthi, Mansi Goel

Proceedings of the 8th IEEE International Conference on Healthcare Informatics, 2020

Quantitative Assessment of Respiratory Distress Using Convolutional Neural Network for Multivariate Time Series Segmentation.

Rohit Pardasani, Rupanjali Chaudhuri, Navchetan Awasthi, Sheetal Chaurasia, Sushma Maya

Proceedings of the Computing in Cardiology, 2020

Classification of 12 Lead ECG Signal Using 1D-Convolutional Neural Network With Class Dependent Threshold.

Rohit Pardasani, Navchetan Awasthi

Proceedings of the Computing in Cardiology, 2020

Multi-threshold Attention U-Net (MTAU) Based Model for Multimodal Brain Tumor Segmentation in MRI Scans.

Navchetan Awasthi, Rohit Pardasani, Swati Gupta

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020