Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore)最新文献

Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study. 胸部 X 光片胸腔疾病的长尾分类：新基准研究

Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore) Pub Date : 2022-09-01 Epub Date: 2022-09-16 DOI: 10.1007/978-3-031-17027-0_3

Gregory Holste, Song Wang, Ziyu Jiang, Thomas C Shen, George Shih, Ronald M Summers, Yifan Peng, Zhangyang Wang

{"title":"Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study.","authors":"Gregory Holste, Song Wang, Ziyu Jiang, Thomas C Shen, George Shih, Ronald M Summers, Yifan Peng, Zhangyang Wang","doi":"10.1007/978-3-031-17027-0_3","DOIUrl":"10.1007/978-3-031-17027-0_3","url":null,"abstract":"Imaging exams, such as chest radiography, will yield a small set of common findings and a much larger set of uncommon findings. While a trained radiologist can learn the visual presentation of rare conditions by studying a few representative examples, teaching a machine to learn from such a \"long-tailed\" distribution is much more difficult, as standard methods would be easily biased toward the most frequent classes. In this paper, we present a comprehensive benchmark study of the long-tailed learning problem in the specific domain of thorax diseases on chest X-rays. We focus on learning from naturally distributed chest X-ray data, optimizing classification accuracy over not only the common \"head\" classes, but also the rare yet critical \"tail\" classes. To accomplish this, we introduce a challenging new long-tailed chest X-ray benchmark to facilitate research on developing long-tailed learning methods for medical image classification. The benchmark consists of two chest X-ray datasets for 19- and 20-way thorax disease classification, containing classes with as many as 53,000 and as few as 7 labeled training images. We evaluate both standard and state-of-the-art long-tailed learning methods on this new benchmark, analyzing which aspects of these methods are most beneficial for long-tailed medical image classification and summarizing insights for future algorithm design. The datasets, trained models, and code are available at https://github.com/VITA-Group/LongTailCXR.","PeriodicalId":93741,"journal":{"name":"Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore)","volume":"13567 ","pages":"22-32"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618235/pdf/nihms-1844023.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40660013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Few-Shot Learning Geometric Ensemble for Multi-label Classification of Chest X-Rays. 胸片多标记分类的少射学习几何集成。

Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore) Pub Date : 2022-09-01 Epub Date: 2022-09-16 DOI: 10.1007/978-3-031-17027-0_12

Dana Moukheiber, Saurabh Mahindre, Lama Moukheiber, Mira Moukheiber, Song Wang, Chunwei Ma, George Shih, Yifan Peng, Mingchen Gao

{"title":"Few-Shot Learning Geometric Ensemble for Multi-label Classification of Chest X-Rays.","authors":"Dana Moukheiber, Saurabh Mahindre, Lama Moukheiber, Mira Moukheiber, Song Wang, Chunwei Ma, George Shih, Yifan Peng, Mingchen Gao","doi":"10.1007/978-3-031-17027-0_12","DOIUrl":"https://doi.org/10.1007/978-3-031-17027-0_12","url":null,"abstract":"This paper aims to identify uncommon cardiothoracic diseases and patterns on chest X-ray images. Training a machine learning model to classify rare diseases with multi-label indications is challenging without sufficient labeled training samples. Our model leverages the information from common diseases and adapts to perform on less common mentions. We propose to use multi-label few-shot learning (FSL) schemes including neighborhood component analysis loss, generating additional samples using distribution calibration and fine-tuning based on multi-label classification loss. We utilize the fact that the widely adopted nearest neighbor-based FSL schemes like ProtoNet are Voronoi diagrams in feature space. In our method, the Voronoi diagrams in the features space generated from multi-label schemes are combined into our geometric DeepVoro Multi-label ensemble. The improved performance in multi-label few-shot classification using the multi-label ensemble is demonstrated in our experiments (The code is publicly available at https://github.com/Saurabh7/Few-shot-learning-multilabel-cxray).","PeriodicalId":93741,"journal":{"name":"Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore)","volume":"13567 ","pages":"112-122"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652771/pdf/nihms-1846293.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40490560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

The Aesthetics of Imperfection in Everyday Life 日常生活中的不完美美学

Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore) Pub Date : 2022-01-01 DOI: 10.5040/9781501380303.ch-001

Yuriko Saito

引用次数: 0

[Essay] The Forced Samaritan: On Face-Distorting Wearable Objects [论文]被迫的撒玛利亚人:关于面部扭曲的可穿戴物品

Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore) Pub Date : 2022-01-01 DOI: 10.5040/9781501380303.ch-011

L. Goralik

引用次数: 0

Afterthought 事后的想法

Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore) Pub Date : 2022-01-01 DOI: 10.5040/9781501380303-006

J. V. D. Zanden

引用次数: 0

The Imperfections of Listing the Past: Listing Names in Holocaust Commemoration 列出过去的不完善之处:在大屠杀纪念活动中列出人名

Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore) Pub Date : 2022-01-01 DOI: 10.5040/9781501380303.ch-008

E. Alphen

引用次数: 0

Promoting the Imperfect: Marketing Strategies to Reduce Product Waste 促进不完美:减少产品浪费的营销策略

Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore) Pub Date : 2022-01-01 DOI: 10.5040/9781501380303.ch-004

Ilona E. De Hooge

引用次数: 2

Imperfect Metamorphoses of Language: Retracing a Childlike Vision with Artist Xu Bing 语言的不完美变形:与艺术家徐冰一起追溯孩童般的视觉

Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore) Pub Date : 2022-01-01 DOI: 10.5040/9781501380303.ch-009

Tingting Hui

引用次数: 0

Polder Panda: Imperfection and Love in Dutch Dairy Farming 圩田熊猫:荷兰奶牛场的不完美与爱

Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore) Pub Date : 2022-01-01 DOI: 10.5040/9781501380303.ch-013

O. Verkaaik

引用次数: 0

Imperfection in Experimental Instruments and Their Performances 实验仪器的缺陷及其性能

Data augmentation, labelling, and imperfections : second MICCAI workshop, DALI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings. DALI (Workshop) (2nd : 2022 : Singapore) Pub Date : 2022-01-01 DOI: 10.5040/9781501380303.ch-006

C. Kelly

引用次数: 0