Literature DB >> 24912370

Computerized detection of breast lesions using deformable part models in ultrasound images.

Gerard Pons1, Robert Martí2, Sergi Ganau3, Melcior Sentís3, Joan Martí2.   

Abstract

Ultrasound imaging is considered an important complementary technique for the screening of dense breasts. Detection of lesions at an early stage is a key step in which computerized lesion detection systems could play an important role in the analysis of US images. In this article, we propose adaptation of a generic object detection technique, deformable part models, to detect lesions in breast US images. The data set used in this study included 326 images, all from different patients (54 malignant lesions, 109 benign lesions and 163 healthy breasts). In terms of lesion detection, our proposal outperformed some of the most relevant approaches described in the literature; we obtained a sensitivity of 86% with 0.28 false-positive detection per image and an Az value of 0.975. In the detection of malignant lesions, our proposed approached had an Az value of 0.93 and a sensitivity of 78% at a 1.15 false-positive detections per image.
Copyright © 2014 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Breast cancer; Cancer detection; Deformable part models; Lesion detection; Ultrasound

Mesh:

Year:  2014        PMID: 24912370     DOI: 10.1016/j.ultrasmedbio.2014.03.005

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  2 in total

1.  Automatic detection of mesiodens on panoramic radiographs using artificial intelligence.

Authors:  Eun-Gyu Ha; Kug Jin Jeon; Young Hyun Kim; Jae-Young Kim; Sang-Sun Han
Journal:  Sci Rep       Date:  2021-11-29       Impact factor: 4.379

Review 2.  BUSIS: A Benchmark for Breast Ultrasound Image Segmentation.

Authors:  Yingtao Zhang; Min Xian; Heng-Da Cheng; Bryar Shareef; Jianrui Ding; Fei Xu; Kuan Huang; Boyu Zhang; Chunping Ning; Ying Wang
Journal:  Healthcare (Basel)       Date:  2022-04-14
  2 in total

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