no code implementations • 8 Sep 2023 • Jakub R. Kaczmarzyk, Alan O'Callaghan, Fiona Inglis, Tahsin Kurc, Rajarsi Gupta, Erich Bremer, Peter Bankhead, Joel H. Saltz
The field of digital pathology has seen a proliferation of deep learning models in recent years.
1 code implementation • 14 Jun 2022 • Jakub R. Kaczmarzyk, Tahsin M. Kurc, Shahira Abousamra, Rajarsi Gupta, Joel H. Saltz, Peter K. Koo
Histopathology remains the gold standard for diagnosis of various cancers.
no code implementations • 23 Apr 2022 • Mahmudul Hasan, Jakub R. Kaczmarzyk, David Paredes, Lyanne Oblein, Jaymie Oentoro, Shahira Abousamra, Michael Horowitz, Dimitris Samaras, Chao Chen, Tahsin Kurc, Kenneth R. Shroyer, Joel Saltz
Understanding the impact of tumor biology on the composition of nearby cells often requires characterizing the impact of biologically distinct tumor regions.
1 code implementation • 3 Dec 2018 • Patrick McClure, Nao Rho, John A. Lee, Jakub R. Kaczmarzyk, Charles Zheng, Satrajit S. Ghosh, Dylan Nielson, Adam G. Thomas, Peter Bandettini, Francisco Pereira
In this paper, we describe a Bayesian deep neural network (DNN) for predicting FreeSurfer segmentations of structural MRI volumes, in minutes rather than hours.
no code implementations • NeurIPS 2018 • Patrick McClure, Charles Y. Zheng, Jakub R. Kaczmarzyk, John A. Lee, Satrajit S. Ghosh, Dylan Nielson, Peter Bandettini, Francisco Pereira
Collecting the large datasets needed to train deep neural networks can be very difficult, particularly for the many applications for which sharing and pooling data is complicated by practical, ethical, or legal concerns.