@inproceedings{800f8597c5f6415fbfdd6abf467c2589,
title = "Automatic histologic grading for lobular carcinoma in situ",
abstract = "Lobular carcinoma in situ (LCIS) causes pathological confusion with other non-invasive histological diagnoses. The study used computational histology to segment relevant objects from the scanned images. Within the collected images from 24 patients, the study shows the accuracy of prediction for LCIS grading. Overall predication accuracy of nuclear grading was 50.56% (p<.001).",
keywords = "Automatic histologic grading, Breast cancer, Lobular carcinoma in situ",
author = "Kim, {S. J.} and Jeong, {H. K.} and Choi, {H. J.} and D. Kim",
year = "2009",
doi = "10.1007/978-3-642-03879-2_184",
language = "English",
isbn = "9783642038785",
series = "IFMBE Proceedings",
number = "2",
pages = "654--657",
booktitle = "World Congress on Medical Physics and Biomedical Engineering",
edition = "2",
note = "World Congress on Medical Physics and Biomedical Engineering: Diagnostic Imaging ; Conference date: 07-09-2009 Through 12-09-2009",
}
