№ files_lp_3_process_9_72069
Conference poster abstract describing the development of large-scale digital pathology and seizure datasets, data acquisition procedures, technical infrastructure, annotation practices, and challenges encountered in building open research corpora.
Authors: J. Smith; S. Jones; M. Smith; J. Doe; B. Smith; J. Jones
Affiliations: Neural Engineering Data Consortium, Temple University, Philadelphia, Pennsylvania, USA; Center for Corporate Research, Acme Corporation, Los Angeles, California, USA; Advanced Technology Laboratory, XYZ Research, New York, New York, USA
Document Type: Conference poster abstract
Subject Area: Seizure detection; digital pathology; biomedical signal processing; deep learning
Institutions Involved: Temple University; Temple University Hospital; Acme Corporation; XYZ Research; National Science Foundation
Project Name: Temple University Digital Pathology Corpus (TUDP); TUSZ Corpus (v1.1.1)
Funding Source: National Science Foundation (CNS1726188; 1925494)
Data Description: High-resolution clinical pathology images in Aperio .svs format with associated pathology reports
Time Frame: Slides dating back to 1997; planned corpus release by December 2020; NSF planning grant January 1, 2020 – June 1, 2021
Technical Resources: Leica Biosystems Aperio AT2 scanner; HPC cluster infrastructure
Intended Audience: Research community in biomedical engineering and signal processing
References Format: IEEE citation style
Conference Context: IEEE Signal Processing in Medicine and Biology Symposium
Price: 8 / 10 USD
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