2024
Mine Your Own Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels
You C, Dai W, Liu F, Min Y, Dvornek N, Li X, Clifton D, Staib L, Duncan J. Mine Your Own Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels. IEEE Transactions On Pattern Analysis And Machine Intelligence 2024, PP: 1-16. PMID: 39269798, DOI: 10.1109/tpami.2024.3461321.Peer-Reviewed Original ResearchMedical image segmentationImage segmentationMedical image segmentation frameworkContext of medical image segmentationLong-tailed class distributionStrong data augmentationsIntra-class variationsSemi-supervised settingData imbalance issueImage segmentation frameworkMedical image analysisMedical image dataSupervision signalsContrastive learningBenchmark datasetsUnsupervised mannerLabel setsData augmentationSegmentation frameworkDomain expertisePseudo-codeImbalance issueModel trainingMedical imagesSegmentation model
2019
ShelfNet for Fast Semantic Segmentation
Zhuang J, Yang J, Gu L, Dvornek N. ShelfNet for Fast Semantic Segmentation. 2019, 00: 847-856. DOI: 10.1109/iccvw.2019.00113.Peer-Reviewed Original ResearchFast semantic segmentationSemantic segmentationCityscapes datasetReal-time segmentation modelStreet-scene understandingFast inference speedEncoder-decoder structurePASCAL VOC datasetHigh accuracyInference speedSkip connectionsAutonomous drivingExtensive experimentsResidual blocksSegmentation modelVOC datasetNovel architectureReal-time methodComputation burdenShallow pathsBiSeNetPSPNetParameter numberComparable speedDataset