ArticleProceedings of the ... IAPR International Conference on Pattern Recognition. International Conference on Pattern Recognition2021
Classifying Breast Histopathology Images with a Ductal Instance-Oriented Pipeline.
Article in Proceedings of the ... IAPR International Conference on Pattern Recognition. International Conference on Pattern Recognition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Improving the Annotation Process in Computational Pathology: A Pilot Study with Manual and Semi-automated Approaches on Consumer and Medical Grade Devices.Journal of imaging informatics in medicine · 2025Article
- A Comprehensive Review of Computer-Aided Models for Breast Cancer Diagnosis Using Histopathology Images.Bioengineering (Basel, Switzerland) · 2023Review
- End-to-End diagnosis of breast biopsy images with transformers.Medical image analysis · 2022Article
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Authors and funding
8 authors.
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Abstract
In this study, we propose the Ductal Instance-Oriented Pipeline (DIOP) that contains a duct-level instance segmentation model, a tissue-level semantic segmentation model, and three-levels of features for diagnostic classification. Based on recent advancements in instance segmentation and the Mask RCNN model, our duct-level segmenter tries to identify each ductal individual inside a microscopic image; then, it extracts tissue-level information from the identified ductal instances. Leveraging three levels of information obtained from these ductal instances and also the histopathology image, the proposed DIOP outperforms previous approaches (both feature-based and CNN-based) in all diagnostic tasks; for the four-way classification task, the DIOP achieves comparable performance to general pathologists in this unique dataset. The proposed DIOP only takes a few seconds to run in the inference time, which could be used interactively on most modern computers. More clinical explorations are needed to study the robustness and generalizability of this system in the future.
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Registered trials
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