05533nam 22007215 450 991034926920332120210130071607.03-030-33850-910.1007/978-3-030-33850-3(CKB)4100000009678320(MiAaPQ)EBC5968218(DE-He213)978-3-030-33850-3(PPN)253256879(EXLCZ)99410000000967832020191024d2019 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierInterpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support[electronic resource] Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings /edited by Kenji Suzuki, Mauricio Reyes, Tanveer Syeda-Mahmood, Ender Konukoglu, Ben Glocker, Roland Wiest, Yaniv Gur, Hayit Greenspan, Anant Madabhushi1st ed. 2019.Cham :Springer International Publishing :Imprint: Springer,2019.1 online resource (xvi, 93 pages)Image Processing, Computer Vision, Pattern Recognition, and Graphics ;11797Includes index.3-030-33849-5 Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC 2019) -- Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer's disease classification -- UBS: A Dimension-Agnostic Metric for Concept Vector Interpretability Applied to Radiomics -- Generation of Multimodal Justification Using Visual Word Constraint Model for Explainable Computer-Aided Diagnosis -- Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection -- Guideline-based Additive Explanation for Computer-Aided Diagnosis of Lung Nodules -- Deep neural network or dermatologist? -- Towards Interpretability of Segmentation Networks by analyzing DeepDreams -- 9th International Workshop on Multimodal Learning for Clinical Decision Support (ML-CDS 2019) -- Towards Automatic Diagnosis from Multi-modal Medical Data -- Deep Learning based Multi-Modal Registration for Retinal Imaging -- Automated Enriched Medical Concept Generation for Chest X-ray Images.This book constitutes the refereed joint proceedings of the Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 7 full papers presented at iMIMIC 2019 and the 3 full papers presented at ML-CDS 2019 were carefully reviewed and selected from 10 submissions to iMIMIC and numerous submissions to ML-CDS. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. .Image Processing, Computer Vision, Pattern Recognition, and Graphics ;11797Artificial intelligenceMathematical logicHealth informaticsOptical data processingArtificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Mathematical Logic and Formal Languageshttps://scigraph.springernature.com/ontologies/product-market-codes/I16048Health Informaticshttps://scigraph.springernature.com/ontologies/product-market-codes/I23060Image Processing and Computer Visionhttps://scigraph.springernature.com/ontologies/product-market-codes/I22021Artificial intelligence.Mathematical logic.Health informatics.Optical data processing.Artificial Intelligence.Mathematical Logic and Formal Languages.Health Informatics.Image Processing and Computer Vision.616.07540285Suzuki Kenjiedthttp://id.loc.gov/vocabulary/relators/edtReyes Mauricioedthttp://id.loc.gov/vocabulary/relators/edtSyeda-Mahmood Tanveeredthttp://id.loc.gov/vocabulary/relators/edtKonukoglu Enderedthttp://id.loc.gov/vocabulary/relators/edtGlocker Benedthttp://id.loc.gov/vocabulary/relators/edtWiest Rolandedthttp://id.loc.gov/vocabulary/relators/edtGur Yanivedthttp://id.loc.gov/vocabulary/relators/edtGreenspan Hayitedthttp://id.loc.gov/vocabulary/relators/edtMadabhushi Anantedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910349269203321Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support2535216UNINA