Histopathological Classification of Breast Cancer Images Using a Multi-Scale Input and Multi-Feature Network
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Department of Computer & Media Engineering, Tongmyong University, Busan 48520, Korea
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Department of Pathology, Ajou University School of Medicine, Ajou University Medical Center, Suwon 16499, Korea
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Author to whom correspondence should be addressed.
Cancers 2020, 12(8), 2031; https://doi.org/10.3390/cancers12082031
Received: 28 May 2020
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Revised: 19 July 2020
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Accepted: 22 July 2020
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Published: 24 July 2020
Diagnosis of pathologies using histopathological images can be time-consuming when many images with different magnification levels need to be analyzed. State-of-the-art computer vision and machine learning methods can help automate the diagnostic pathology workflow and thus reduce the analysis time. Automated systems can also be more efficient and accurate, and can increase the objectivity of diagnosis by reducing operator variability. We propose a multi-scale input and multi-feature network (MSI-MFNet) model, which can learn the overall structures and texture features of different scale tissues by fusing multi-resolution hierarchical feature maps from the network’s dense connectivity structure. The MSI-MFNet predicts the probability of a disease on the patch and image levels. We evaluated the performance of our proposed model on two public benchmark datasets. Furthermore, through ablation studies of the model, we found that multi-scale input and multi-feature maps play an important role in improving the performance of the model. Our proposed model outperformed the existing state-of-the-art models by demonstrating better accuracy, sensitivity, and specificity.
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Keywords:
breast histopathology; computer-assisted diagnosis; whole slide imaging; multi-class classification; data augmentation
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MDPI and ACS Style
Sheikh, T.S.; Lee, Y.; Cho, M. Histopathological Classification of Breast Cancer Images Using a Multi-Scale Input and Multi-Feature Network. Cancers 2020, 12, 2031. https://doi.org/10.3390/cancers12082031
AMA Style
Sheikh TS, Lee Y, Cho M. Histopathological Classification of Breast Cancer Images Using a Multi-Scale Input and Multi-Feature Network. Cancers. 2020; 12(8):2031. https://doi.org/10.3390/cancers12082031
Chicago/Turabian StyleSheikh, Taimoor S., Yonghee Lee, and Migyung Cho. 2020. "Histopathological Classification of Breast Cancer Images Using a Multi-Scale Input and Multi-Feature Network" Cancers 12, no. 8: 2031. https://doi.org/10.3390/cancers12082031
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