Improving Deep Lesion Detection Using 3D Contextual and Spatial Attention
| Autor: | Qingyi Tao, Jianfei Cai, Zongyuan Ge, Jianxiong Yin, Simon See |
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| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry 0206 medical engineering Detector Pattern recognition 02 engineering and technology 010501 environmental sciences 020601 biomedical engineering 01 natural sciences Object detection Lesion Feature (computer vision) medicine Deep Lesion Overhead (computing) Artificial intelligence medicine.symptom Focus (optics) business Feature learning 0105 earth and related environmental sciences |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030322250 MICCAI (6) |
| DOI: | 10.1007/978-3-030-32226-7_21 |
| Popis: | Lesion detection from computed tomography (CT) scans is challenging compared to natural object detection because of two major reasons: small lesion size and small inter-class variation. Firstly, the lesions usually only occupy a small region in the CT image. The feature of such small region may not be able to provide sufficient information due to its limited spatial feature resolution. Secondly, in CT scans, the lesions are often indistinguishable from the background since the lesion and non-lesion areas may have very similar appearances. To tackle both problems, we need to enrich the feature representation and improve the feature discriminativeness. Therefore, we introduce a dual-attention mechanism to the 3D contextual lesion detection framework, including the cross-slice contextual attention to selectively aggregate the information from different slices through a soft re-sampling process. Moreover, we propose intra-slice spatial attention to focus the feature learning in the most prominent regions. Our method can be easily trained end-to-end without adding heavy overhead on the base detection network. We use DeepLesion dataset and train a universal lesion detector to detect all kinds of lesions such as liver tumors, lung nodules, and so on. The results show that our model can significantly boost the results of the baseline lesion detector (with 3D contextual information) but using much fewer slices. |
| Databáze: | OpenAIRE |
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