Skin lesion classification using weakly-supervised fine-grained method

Xi Xue, Sei Ichiro Kamata, Daming Luo

研究成果: Conference contribution

2 被引用数 (Scopus)


In recent years, skin cancer has become one of the most common cancers. Among all types of skin cancers, melanoma is the most fatal one and many people die of this disease every year. Early detection can greatly reduce the death rate and save more lives. Skin lesions are one of the early symptoms of melanoma and other types of skin cancer. So accurately recognizing various skin lesions in early stage is of great significance. There have been lots of existing works based on convolutional neural networks (CNN) to solve skin lesion classification but seldom do they involve the similarity among different lesions. For example, we find that some lesions like melanoma and nevi look similar in appearance which is hard for neural network to distinguish categories of skin lesions. Inspired by fine-grained image classification, we propose a novel network to distinguish each category accurately. In our paper, we design an effective module, distinct region proposal module (DRPM), to extract the distinct regions from each image. Spatial attention and channel-wise attention are both utilized to enrich feature maps and guide the network to focus on the highlighted areas in a weakly-supervised way. In addition, two preprocessing steps are added to ensure the network to get better results. We demonstrate the potential of the proposed method on ISIC 2017 dataset. Experiments show that our approach is effective and efficient.

ホスト出版物のタイトルProceedings of ICPR 2020 - 25th International Conference on Pattern Recognition
出版社Institute of Electrical and Electronics Engineers Inc.
出版ステータスPublished - 2020
イベント25th International Conference on Pattern Recognition, ICPR 2020 - Virtual, Milan, Italy
継続期間: 2021 1月 102021 1月 15


名前Proceedings - International Conference on Pattern Recognition


Conference25th International Conference on Pattern Recognition, ICPR 2020
CityVirtual, Milan

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識


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