Stem mammogram$ (all stems)

15 papers:

ICPR-2014-AghdamPS #adaptation #probability #segmentation

Adaptive Probabilistic Thresholding Method for Accurate Breast Region Segmentation in Mammograms (HHA, DP, AS), pp. 3357–3362.

ICEIS-AIDSS-2010-WatanabeRTT #classification #statistics

Statistical Associative Classification of Mammograms — The SACMiner Method (CYVW, MXR, CTJ, AJMT), pp. 121–128.

ICPR-2010-BoucherCVJ #visual notation

Visual Perception Driven Registration of Mammograms (AB, FC, NV, PJ), pp. 2374–2377.

ICPR-2010-HarirchiRMDG #algorithm #detection #using

Two-Level Algorithm for MCs Detection in Mammograms Using Diverse-Adaboost-SVM (FH, PR, HAM, FD, MG), pp. 269–272.

ICPR-2008-HaindlM #segmentation

Unsupervised mammograms segmentation (MH, SM), pp. 1–4.

ICPR-2008-WuJP #detection #effectiveness #linear

Effective features based on normal linear structures for detecting microcalcifications in mammograms (ZQW, JJ, YP), pp. 1–4.

MLDM-2007-MartinsSSPG #classification #image #using

Classification of Breast Masses in Mammogram Images Using Ripley’s K Function and Support Vector Machine (LdOM, ECdS, ACS, ACdP, MG), pp. 784–794.

SAC-2007-YapaK #algorithm #component #image

A connected component labeling algorithm for grayscale images and application of the algorithm on mammograms (RDY, HK), pp. 146–152.

SAC-2006-FelipeRSTT #classification #effectiveness #retrieval

Effective shape-based retrieval and classification of mammograms (JCF, MXR, EPMdS, AJMT, CTJ), pp. 250–255.

ICPR-v3-2004-DEliaMMPST #classification #clustering #detection #segmentation

Detection of Microcalcifications Clusters in Mammograms through TS-MRF Segmentation and SVM-based Classification (CD, CM, MM, GP, GS, FT), pp. 742–745.

SAC-2004-Przelaskowski

Compression of mammograms for medical practice (AP), pp. 249–253.

ICPR-v1-2000-Rodriguez-SanchezGFF #how

How to Define the Notion of Microcalcifications in Digitized Mammograms (RRS, JAG, JFV, XRFV), pp. 1494–1499.

ICPR-v2-2000-BovisS #detection #using

Detection of Masses in Mammograms Using Texture Features (KB, SS), pp. 2267–2270.

ICPR-v4-2000-CordellaTV #clustering

Combining Experts with Different Features for Classifying Clustered Microcalcifications in Mammograms (LPC, FT, MV), pp. 4324–4327.

ICPR-1996-ChenL96a #analysis #multi

A multiresolution wavelet analysis of digital mammograms (CHC, GGL), pp. 710–714.