Multiple Field-of-View Based Attention Driven Network for Weakly Supervised Common Bile Duct Stone Detection.
IEEE J Transl Eng Health Med
; 11: 394-404, 2023.
Article
em En
| MEDLINE
| ID: mdl-37465459
ABSTRACT
OBJECTIVE:
Common bile duct (CBD) stones caused diseases are life-threatening. Because CBD stones locate in the distal part of the CBD and have relatively small sizes, detecting CBD stones from CT scans is a challenging issue in the medical domain. METHODS AND PROCEDURES We propose a deep learning based weakly-supervised method called multiple field-of-view based attention driven network (MFADNet) to detect CBD stones from CT scans based on image-level labels. Three dominant modules including a multiple field-of-view encoder, an attention driven decoder and a classification network are collaborated in the network. The encoder learns the feature of multi-scale contextual information while the decoder with the classification network is applied to locate the CBD stones based on spatial-channel attentions. To drive the learning of the whole network in a weakly-supervised and end-to-end trainable manner, four losses including the foreground loss, background loss, consistency loss and classification loss are proposed.RESULTS:
Compared with state-of-the-art weakly-supervised methods in the experiments, the proposed method can accurately classify and locate CBD stones based on the quantitative and qualitative results.CONCLUSION:
We propose a novel multiple field-of-view based attention driven network for a new medical application of CBD stone detection from CT scans while only image-levels are required to reduce the burdens of labeling and help physicians automatically diagnose CBD stones. The source code is available at https//github.com/nchucvml/MFADNet after acceptance. CLINICAL IMPACT Our deep learning method can help physicians localize relatively small CBD stones for effectively diagnosing CBD stone caused diseases.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Cálculos Biliares
/
Doenças do Ducto Colédoco
/
Coledocolitíase
Tipo de estudo:
Diagnostic_studies
/
Qualitative_research
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article