Structure-Aware Staging for Breast Cancer Metastases

Zhang, Songtao1; Sun, Li1; Wang, Ruiqiao1; Tang, Hongping2; Zhang, Jin1; Luo, Lin3

10.1007/978-3-030-00946-5_13

2018

16113349

1611-3349

IMAGE ANALYSIS FOR MOVING ORGAN, BREAST, AND THORACIC IMAGES

11040

116-123

Granada, Spain

GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND

SPRINGER INTERNATIONAL PUBLISHING AG

Determining the stage of breast cancer metastases is an important component of cancer surveillance and control. It is laborious for pathologist to manually examine large amount of biological tissue and this process is error-prone. Deep learning methods can be used to automatically detect cancer metastases and identify cancer subtypes. However, current deep learning-based methods mainly focus on local patches but ignore the overall structure of lymph tissue, due to the memory limitation and computational cost of processing the gigapixel whole slide histopathological image (WSI) at a time. In this paper, we propose a structure-aware deep learning framework for staging of breast cancer metastases, in which we introduce lymph structure information to guide training patch selection and prediction features design. Our approach achieves 85.1% accuracy on slide-level and 0.80 kappa score on patient level. In addition, we see 6.1% and 5% performance gain on slide level and patient level classification respectively after introducing global structure information.

Cancer staging Structure-aware Deep learning

第一

英语

CPCI-S ; EI

Computer Science ; Imaging Science & Photographic Technology

Computer Science, Theory & Methods ; Imaging Science & Photographic Technology

WOS:000477764700013

20184005884287

Body fluids ; Classification (of information) ; Computer aided analysis ; Deep learning ; Diseases ; Image analysis ; Pathology ; Tissue

Biological Materials and Tissue Engineering:461.2 ; Medicine and Pharmacology:461.6 ; Information Theory and Signal Processing:716.1 ; Computer Applications:723.5 ; Imaging Techniques:746

Web of Science

1.Southern Univ Sci & Technol, Shenzhen 518055, Peoples R China
2.Southern Med Univ, Shenzhen Matern & Child Healthcare Hosp, Dept Pathol, Shenzhen 518028, Peoples R China
3.Peking Univ, Beijing 100871, Peoples R China

Zhang, Songtao,Sun, Li,Wang, Ruiqiao,et al. Structure-Aware Staging for Breast Cancer Metastases[C]. GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND:SPRINGER INTERNATIONAL PUBLISHING AG,2018:116-123.