Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks

Autor: Moi Hoon, Yap, Gerard, Pons, Joan, Marti, Sergi, Ganau, Melcior, Sentis, Reyer, Zwiggelaar, Adrian K, Davison, Robert, Marti, Moi Hoon Yap

Publikováno v: O2, repositorio institucional de la UOC
Universitat Oberta de Catalunya (UOC)
Yap, M H, Pons, G, Martí, J, Ganau, S, Sentís, M, Zwiggelaar, R, Davison, A K & Martí, R 2018, ' Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks ', IEEE Journal of Biomedical and Health Informatics, vol. 22, no. 4, pp. 1218-1226 . https://doi.org/10.1109/JBHI.2017.2731873

Breast lesion detection using ultrasound imaging is considered an important step of computer-aided diagnosis systems. Over the past decade, researchers have demonstrated the possibilities to automate the initial lesion detection. However, the lack of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4fd5f7582ec713be76db77bd6a9c2a40
https://doi.org/10.1109/jbhi.2017.2731873

Segmentation d'images robuste appliqué à l'imagerie par résonance magnétique et l'échographie de la prostate

Autor: Ghose, Soumya

Publikováno v: TDX (Tesis Doctorals en Xarxa)
TDR. Tesis Doctorales en Red
instname
Human health and pathology. Université de Bourgogne, 2012. English. 〈NNT : 2012DIJOS039〉
DUGiDocs – Universitat de Girona
Human health and pathology. Université de Bourgogne, 2012. English. ⟨NNT : 2012DIJOS039⟩

Prostate segmentation in trans rectal ultrasound (TRUS) and magnetic resonanceimages (MRI) facilitates volume estimation, multi-modal image registration, surgicalplaning and image guided prostate biopsies. The objective of this thesis is to developsh

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::4975f9b24fd925a792975988b43a1aa9
http://hdl.handle.net/10803/98524