DOI: 10.5061/dryad.jm6k3
title: Data from: A novel cascade classifier for automatic microcalcification detection

description: In this paper, we present a novel cascaded classification framework for
 automatic detection of individual and clusters of microcalcifications
 (μC). Our framework comprises three classification stages: i) a random
 forest (RF) classifier for simple features capturing the second order
 local structure of individual μCs, where non-μC pixels in the target
 mammogram are efficiently eliminated; ii) a more complex discriminative
 restricted Boltzmann machine (DRBM) classifier for μC candidates
 determined in the RF stage, which automatically learns the detailed
 morphology of μC appearances for improved discriminative power; and iii) a
 detector to detect clusters of μCs from the individual μC detection
 results, using two different criteria. From the two-stage RF-DRBM
 classifier, we are able to distinguish μCs using explicitly computed
 features, as well as learn implicit features that are able to further
 discriminate between confusing cases. Experimental evaluation is conducted
 on the original Mammographic Image Analysis Society (MIAS) and mini-MIAS
 databases, as well as our own Seoul National University Bundang Hospital
 digital mammographic database. It is shown that the proposed method
 outperforms comparable methods in terms of receiver operating
 characteristic (ROC) and precision-recall curves for detection of
 individual μCs and free-response receiver operating characteristic (FROC)
 curve for detection of clustered μCs.
description: MIAS DB - File
 1The
 Mammographic Image Analysis Society Digital Mammographic Database *
 Approval for redistribution provided by J. Suckling (js369@cam.ac.uk)
 CREDITS: Organiser: J Suckling; Truth-Data: C R M Boggis and I Hutt;
 Co-Workers: S Astley, D Betal, N Cerneaz, D R Dance, S-L Kok, J Parker, I
 Ricketts, J Savage, E Stamatakis and P Taylor. Special Thanks: N
 Karrsemeijer. ========================================================
 REFERENCE: J Suckling et al (1994) "The Mammographic Image Analysis
 Society Digital Mammogram Database" Exerpta Medica. International
 Congress Series 1069 pp 375-378.
 ========================================================MIAS-DB.zipMIAS DB - File 2The Mammographic Image Analysis Society Digital Mammographic Database * Approval for redistribution provided by J. Suckling (js369@cam.ac.uk) CREDITS: Organiser: J Suckling; Truth-Data: C R M Boggis and I Hutt; Co-Workers: S Astley, D Betal, N Cerneaz, D R Dance, S-L Kok, J Parker, I Ricketts, J Savage, E Stamatakis and P Taylor. Special Thanks: N Karrsemeijer. ========================================================= REFERENCE: J Suckling et al (1994) "The Mammographic Image Analysis Society Digital Mammogram Database" Exerpta Medica. International Congress Series 1069 pp 375-378. =========================================================MIAS-DB.z01SNUBH-MDB-mCiThe Seoul National University Bundang Hospital Digital Mammographic Database - with Individual MC Annotations (SNUBH-MDB-mCi) See also our webpage at http://cv.snu.ac.kr/research/cascade-mc-detector15/index.html for updated information. For questions regarding data, e-mail: syshin@snu.ac.kr INFORMATION: 1) The size of all images are 1914 pixels x 2294 pixels. 2) This zip-file contains 49 mammograms with micro-calcifications (μCs) and corresponding annotations for individual μCs and μC clusters. - The files named as '****_i.txt' are annotation files for individual μCs and list (x,y) coordinates of each μC. - The files named as '****_c.txt' are annotation files for μC clusters and list bounding boxes of each μC cluster. A bounding box is represented as two (x,y) coordinates, upper left corner and lower right corner. - Coordinate system origin is the upper-left corner.SNUBH-MDB-μCi.zipAnnotations of Individual Microcalcification in mini-MIAS DBThese files contain image pixel coordinates of individual microcalcifications in the images from the mini-MIAS database, available from http://peipa.essex.ac.uk/info/mias.html. The file name corresponds to the particular image name in the mini-MIAS database. See also our webpage at http://cv.snu.ac.kr/research/cascade-mc-detector15/index.html for updated information. For questions regarding data, e-mail: syshin@snu.ac.krmini-MIAS-ind_μC-annotations.zip