{"title":"伤口分期分类的细粒度跨层注意框架","authors":"Keval Nagda, M. Briden, Narges Norouzi","doi":"10.1109/BHI56158.2022.9926798","DOIUrl":null,"url":null,"abstract":"Determining progress during wound healing is crucial for effective diagnosis and treatment. Previous works have solved this task using methods paying attention to specific regions of the image. However, we explore an alternative, non-local attention approach and implement a cross-layer attention mechanism that focuses on the areas of interest and considers related spatial regions of the wound. Experimental results and visual representations show that adding cross-layer modules to mid-level and top-level layers enables better classification of wound healing stage and generalization.","PeriodicalId":347210,"journal":{"name":"2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fine-grained Cross-Layer Attention Framework for Wound Stage Classification\",\"authors\":\"Keval Nagda, M. Briden, Narges Norouzi\",\"doi\":\"10.1109/BHI56158.2022.9926798\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Determining progress during wound healing is crucial for effective diagnosis and treatment. Previous works have solved this task using methods paying attention to specific regions of the image. However, we explore an alternative, non-local attention approach and implement a cross-layer attention mechanism that focuses on the areas of interest and considers related spatial regions of the wound. Experimental results and visual representations show that adding cross-layer modules to mid-level and top-level layers enables better classification of wound healing stage and generalization.\",\"PeriodicalId\":347210,\"journal\":{\"name\":\"2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BHI56158.2022.9926798\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BHI56158.2022.9926798","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fine-grained Cross-Layer Attention Framework for Wound Stage Classification
Determining progress during wound healing is crucial for effective diagnosis and treatment. Previous works have solved this task using methods paying attention to specific regions of the image. However, we explore an alternative, non-local attention approach and implement a cross-layer attention mechanism that focuses on the areas of interest and considers related spatial regions of the wound. Experimental results and visual representations show that adding cross-layer modules to mid-level and top-level layers enables better classification of wound healing stage and generalization.