Large-scale, multi-site collaboration is becoming indispensable for a wide range of research and clinical activities including tissue banking, proteomics, and outcome studies. Future progress in several key areas will rely on the capacity of individuals to dynamically acquire, share and assess images and correlated data. The main objective of this proposal is to develop, evaluate, and maintain PathMiner, a web-based model for interactive telemedicine, intelligent archiving, and automated decision support in pathology. The major components of PathMiner are a distributed telemicroscopy subsystem (DT), an intelligent archival (IA) subsystem and an Image Guided Decision Support (IGDS) subsystem. The DT subsystem enables users to control robotic microscopes, remotely, while the imaged specimen is broadcast to participants. It features entropy-based, auto-focusing, shared graphics, and messaging. The IA subsystem performs multivariate indexing and remote management of databases. The IGDS subsystem supports submission of queries across networks in order to automatically locate and retrieve digitized pathology specimens and correlated molecular studies of those cases from within distributed """"""""ground-truth"""""""" databases which exhibit spectral and spatial profiles which are consistent with the query image. During preliminary studies, a prototype correctly discriminated among three commonly confused hematologic malignancies and normal cells in more than 83% of the cases using a mixed database of 1,900 test cells. The University of Medicine and Dentistry of NJ, Rutgers University, and the University of Pennsylvania School of Medicine will collaborate to 1) develop the means for populating ground-truth databases with new cases in multi-user environments; 2) expand ground-truth databases with a broader spectrum of hematologic disorders; 3) develop the means for unsupervised specimen analysis and determine the relationship between morphologic and clinical (protein/molecular) profiles; 4) determine confidence intervals in feature space for the spectrum of malignancies; 5) develop aweb interface for PazhMiner to coordinate flow of data and objects among subsystems; 6) conduct multi-site prospective performance studies and make PathMiner and the ground truth databases available as shareable resources for collaborative research, education and clinical decision support.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Research Project (R01)
Project #
5R01LM007455-03
Application #
6801035
Study Section
Biomedical Library and Informatics Review Committee (BLR)
Program Officer
Florance, Valerie
Project Start
2002-09-30
Project End
2006-09-30
Budget Start
2004-09-30
Budget End
2006-09-30
Support Year
3
Fiscal Year
2004
Total Cost
$219,179
Indirect Cost
Name
University of Medicine & Dentistry of NJ
Department
Pathology
Type
Schools of Medicine
DUNS #
617022384
City
Piscataway
State
NJ
Country
United States
Zip Code
08854
Yang, Lin; Tuzel, Oncel; Chen, Wenjin et al. (2009) PathMiner: a Web-based tool for computer-assisted diagnostics in pathology. IEEE Trans Inf Technol Biomed 13:291-9
Yang, Lin; Meer, Peter; Foran, David J (2007) Multiple Class Segmentation Using A Unified Framework over Mean-Shift Patches. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit 2007:1-8
Hall, Bonnie; Chen, Wenjin; Reiss, Michael et al. (2007) A clinically motivated 2-fold framework for quantifying and classifying immunohistochemically stained specimens. Med Image Comput Comput Assist Interv 10:287-94
Tuzel, Oncel; Yang, Lin; Meer, Peter et al. (2007) Classification of hematologic malignancies using texton signatures. Pattern Anal Appl 10:277-290
Yang, Lin; Chen, Wenjin; Meer, Peter et al. (2007) High throughput analysis of breast cancer specimens on the grid. Med Image Comput Comput Assist Interv 10:617-25
Yang, Lin; Foran, David J (2006) A VARIATIONAL FRAMEWORK FOR PARTIALLY OCCLUDED IMAGE SEGMENTATION USING COARSE TO FINE SHAPE ALIGNMENT AND SEMI-PARAMETRIC DENSITY APPROXIMATION. Proc Int Conf Image Proc 1:137-140
Chen, Wenjin; Foran, David J (2006) Advances in cancer tissue microarray technology: Towards improved understanding and diagnostics. Anal Chim Acta 564:74-81
Chen, Wenjin; Meer, Peter; Georgescu, Bogdan et al. (2005) Image mining for investigative pathology using optimized feature extraction and data fusion. Comput Methods Programs Biomed 79:59-72
Yang, Lin; Meer, Peter; Foran, David J (2005) Unsupervised segmentation based on robust estimation and color active contour models. IEEE Trans Inf Technol Biomed 9:475-86
Chen, Wenjin; Reiss, Michael; Foran, David J (2004) A prototype for unsupervised analysis of tissue microarrays for cancer research and diagnostics. IEEE Trans Inf Technol Biomed 8:89-96

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