paper-with-me

홈 › Papers

The University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM) Dataset

2021-08-30 · Evan Calabrese, Javier E. Villanueva-Meyer, Jeffrey D. Rudie, Andreas M. Rauschecker, Ujjwal Baid, Spyridon Bakas, Soonmee Cha, John T. Mongan, Christopher P. Hess

Here we present the University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM) dataset. The UCSF-PDGM dataset includes 500 subjects with histopathologically-proven diffuse gliomas who were imaged with a standardized 3 Tesla preoperative brain tumor MRI protocol featuring predominantly 3D imaging, as well as advanced diffusion and perfusion imaging techniques. The dataset also includes isocitrate dehydrogenase (IDH) mutation status for all cases and O6-methylguanine-DNA methyltransferase (MGMT) promotor methylation status for World Health Organization (WHO) grade III and IV gliomas. The UCSF-PDGM has been made publicly available in the hopes that researchers around the world will use these data to continue to push the boundaries of AI applications for diffuse gliomas.

📄 PDF Abstract BibTeX arXiv:2109.00356

Code (0)

등록된 구현이 없습니다.

Methods 이 논문이 사용한 방법론

Diffusion Diffusion models generate samples by gradually removing noise from a signal, and their training objective can be expressed as a reweighted variational lower-bound…

Similar Papers 제목 키워드 기반

The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset

2023-04-14 · Jeffrey D. Rudie, Rachit Saluja, David A. Weiss, Pierre Nedelec 외

The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) dataset is a public, clinical, multimodal brain MRI dataset consisting of 560 brain MRIs from 412 patients with expert ann…

Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging

2023-03-23 · Todd C. Hollon, Cheng Jiang, Asadur Chowdury, Mustafa Nasir-Moin 외

Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. However, timely molecular diagnostic testing for patients with brain tumors is…

DiagnosticManagement

Stack-U-Net: Refinement Network for Image Segmentation on the Example of Optic Disc and Cup

2018-04-30 · Artem Sevastopolsky, Stepan Drapak, Konstantin Kiselev, Blake M. Snyder 외

In this work, we propose a special cascade network for image segmentation, which is based on the U-Net networks as building blocks and the idea of the iterative refinement. The model was mainly applied to achieve higher …

Image SegmentationSegmentationSemantic Segmentation

Multi-task Learning of Histology and Molecular Markers for Classifying Diffuse Glioma

2023-03-26 · Xiaofei Wang, Stephen Price, Chao Li

Most recently, the pathology diagnosis of cancer is shifting to integrating molecular makers with histology features. It is a urgent need for digital pathology methods to effectively integrate molecular markers with hist…

Multi-Task Learningwhole slide images

Integrative Imaging Informatics for Cancer Research: Workflow Automation for Neuro-oncology (I3CR-WANO)

2022-10-06 · Satrajit Chakrabarty, Syed Amaan Abidi, Mina Mousa, Mahati Mokkarala 외

Efforts to utilize growing volumes of clinical imaging data to generate tumor evaluations continue to require significant manual data wrangling owing to the data heterogeneity. Here, we propose an artificial intelligence…

SegmentationTumor Segmentation