DEEP KEYPOINT DETECTION FOR THE AESTHETIC EVALUATION OF BREAST CANCER SURGERY OUTCOMES

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2019

Autores

Wilson Silva (Autor) Outra; Eduardo Castro (Autor) Outra; Maria J. Cardoso (Autor) Outra; Florian Fitzal (Autor) Outra; Jaime S. Cardoso (Autor) FEUP

Ata de Conferência Internacional

Título: 2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019)

Páginas: 1082-1086

16th IEEE International Symposium on Biomedical Imaging (ISBI)

Venice, ITALY, APR 08-11, 2019

Indexação

ISI Web of Knowledge - 4 Citações

Scopus - 8 Citações

Outras Informações

ID Authenticus: P-00R-2YH

DOI: 10.1109/isbi.2019.8759331

Abstract (EN): Breast cancer high survival rate led to an increased interest in the quality of life after treatment, particularly regarding the aesthetic outcome. Currently used aesthetic assessment methods are subjective, which make reproducibility and impartiality impossible. To create an objective method capable of being selected as the gold standard, it is fundamental to detect, in a completely automatic manner, keypoints in photographs of women's torso after being subjected to breast cancer surgeries. This paper proposes a deep and a hybrid model to detect keypoints with high accuracy. Our methods are tested on two datasets, one composed of images with a clean and consistent background and a second one that contains photographs taken under poor lighting and background conditions. The proposed methods represent an improvement in the detection of endpoints, nipples and breast contour for both datasets in terms of average error distance when compared with the current state-of-the-art.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 5