LEADER 03945nam 22007455 450 001 9910595032503321 005 20251225201926.0 010 $a9783031170270 010 $a303117027X 024 7 $a10.1007/978-3-031-17027-0 035 $a(CKB)5850000000078348 035 $a(MiAaPQ)EBC7102130 035 $a(Au-PeEL)EBL7102130 035 $a(PPN)264953274 035 $a(BIP)85784444 035 $a(BIP)85408879 035 $a(DE-He213)978-3-031-17027-0 035 $a(EXLCZ)995850000000078348 100 $a20220921d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Augmentation, Labelling, and Imperfections $eSecond MICCAI Workshop, DALI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings /$fedited by Hien V. Nguyen, Sharon X. Huang, Yuan Xue 205 $a1st ed. 2022. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2022. 215 $a1 online resource (134 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v13567 300 $aIncludes index. 311 08$a9783031170263 311 08$a3031170261 327 $aImage Synthesis-based Late Stage Cancer Augmentation and Semi-Supervised Segmentation for MRI Rectal Cancer Staging -- DeepEdit: Deep Editable Learning for Interactive Segmentation of 3D Medical Images -- Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study -- Lesser of Two Evils Improves Learning in the Context of Cortical Thickness Estimation Models - Choose Wisely -- TAAL: Test-time Augmentation for Active Learning in Medical Image Segmentation -- Disentangling A Single MR Modality -- CTooth+: A Large-scale Dental Cone Beam Computed Tomography Dataset and Benchmark for Tooth Volume Segmentation -- Noisy Label Classification using Label Noise Selection with Test-Time Augmentation Cross-Entropy and NoiseMix Learning -- CSGAN: Synthesis-Aided Brain MRI Segmentation on 6-Month Infants -- A Stratified Cascaded Approach for Brain Tumor Segmentation with the Aid of Multi-modal Synthetic Data -- Efficient Medical Image Assessment via Self-supervised Learning -- Few-ShotLearning Geometric Ensemble for Multi-label Classification of Chest X-rays. 330 $aThis book constitutes the refereed proceedings of the Second MICCAI Workshop on Data Augmentation, Labelling, and Imperfections, DALI 2022, held in conjunction with MICCAI 2022, in Singapore in September 2022. DALI 2022 accepted 12 papers from the 22 submissions that were reviewed. The papers focus on rigorous study of medical data related to machine learning systems. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v13567 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aArtificial intelligence 606 $aComputers 606 $aApplication software 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aArtificial Intelligence 606 $aComputing Milieux 606 $aComputer and Information Systems Applications 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 0$aArtificial intelligence. 615 0$aComputers. 615 0$aApplication software. 615 14$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aArtificial Intelligence. 615 24$aComputing Milieux. 615 24$aComputer and Information Systems Applications. 676 $a616.0754 676 $a610.285631 702 $aHuang$b Sharon X. 702 $aXue$b Yuan 702 $aNguyen$b Hien V. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910595032503321 996 $aData augmentation, labelling, and imperfections$93023491 997 $aUNINA