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Article overview
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Automatic Application Level Set Approach in Detection Calcifications in Mammographic Image | Atef Boujelben
; Hedi Tmar
; Jameleddine Mnif
; Mohamed Abid
; | Date: |
1 Sep 2011 | Abstract: | Breast cancer is considered as one of a major health problem that constitutes
the strongest cause behind mortality among women in the world. So, in this
decade, breast cancer is the second most common type of cancer, in term of
appearance frequency, and the fifth most common cause of cancer related death.
In order to reduce the workload on radiologists, a variety of CAD systems;
Computer-Aided Diagnosis (CADi) and Computer-Aided Detection (CADe) have been
proposed. In this paper, we interested on CADe tool to help radiologist to
detect cancer. The proposed CADe is based on a three-step work flow; namely,
detection, analysis and classification. This paper deals with the problem of
automatic detection of Region Of Interest (ROI) based on Level Set approach
depended on edge and region criteria. This approach gives good visual
information from the radiologist. After that, the features extraction using
textures characteristics and the vector classification using Multilayer
Perception (MLP) and k-Nearest Neighbours (KNN) are adopted to distinguish
different ACR (American College of Radiology) classification. Moreover, we use
the Digital Database for Screening Mammography (DDSM) for experiments and these
results in term of accuracy varied between 60 % and 70% are acceptable and must
be ameliorated to aid radiologist. | Source: | arXiv, 1109.0138 | Services: | Forum | Review | PDF | Favorites |
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