Azim Laiwalla

According to our database, Azim Laiwalla authored at least 4 papers between 2021 and 2023.

Collaborative distances:

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

2023

Segmentation and identification of fatty infiltration of the erector spinae using deep learning.

Anshul Ratnaparkhi, Bilwaj Gaonkar, Azim Laiwalla, Elliot Berdy, Matiar Jafari, Abhinav Suri, David Zarrin, Kirstin Cook, Bayard Wilson, Luke Macyszyn, Joel Beckett

Proceedings of the Medical Imaging 2023: Image Processing, 2023

2022

A deep network ensemble for segmentation of cervical spinal cord and neural foramina.

David Zarrin, Anshul Ratnaparkhi, Bayard Wilson, Kirstin Cook, Ien Li, Azim Laiwalla, Mark Attiah, Joel Beckett, Bilwaj Gaonkar, Luke Macyszyn

Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022

Ensembling mitigates scanner effects in deep learning medical image segmentation with deep-U-Nets.

Anshul Ratnaparkhi, Bilwaj Gaonkar, David Zarrin, Ien Li, Kirstin Cook, Azim Laiwalla, Bayard Wilson, Mark Attiah, Christine S. Ahn, Diane Villaroman, Bryan Yoo, Banafsheh Salehi, Joel Beckett, Luke Macyszyn

Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022

2021

Eigenrank by committee: Von-Neumann entropy based data subset selection and failure prediction for deep learning based medical image segmentation.

Bilwaj Gaonkar, Joel Beckett, Mark Attiah, Christine S. Ahn, Matthew Edwards, Bayard Wilson, Azim Laiwalla, Banafsheh Salehi, Bryan Yoo, Alex A. T. Bui, Luke Macyszyn

Medical Image Anal., 2021