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  title info:
    title: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
    sub title: 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings
  name:
    name part: Stoyanov, Danail
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    name part: Taylor, Zeike
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    name part: Carneiro, Gustavo
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    name part: Syeda-Mahmood, Tanveer
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    name part: Martel, Anne
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    name part: Tavares, João Manuel R. S.
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    name part: Papa, João Paulo
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  name:
    name part: Belagiannis, Vasileios
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  name:
    name part: Nascimento, Jacinto C.
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  name:
    name part: Lü, Zhi
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  name:
    name part: Conjeti, Sailesh
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  name:
    name part: Moradi, Mehdi
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    name part: Greenspan, Hayit
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  name:
    name part: Madabhushi, Anant
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  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: gw
    date issued: 2018
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (XVII, 387 pages 159 illustrations) : online resource.
  abstract: This book constitutes the refereed joint proceedings of the 4th International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2018, and the 8th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 39 full papers presented at DLMIA 2018 and the 4 full papers presented at ML-CDS 2018 were carefully reviewed and selected from 85 submissions to DLMIA and 6 submissions to ML-CDS. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.
  table of contents: Semi-Automated Extraction of Crohns Disease MR Imaging Markers using a 3D Residual CNN with Distance Prior -- Weakly Supervised Localisation for Fetal Ultrasound Images -- Learning to Decode 7T-like MR Image Reconstruction from 3T MR Images -- Segmentation of Head and Neck Organs-At-Risk in Longitudinal CT Scans Combining Deformable Registrations and Convolutional Neural Networks -- Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease -- Contextual Additive Networks to Efficiently Boost 3D Image Segmentations -- Longitudinal detection of radiological abnormalities with time-modulated LSTM -- SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays -- Active Learning for Segmentation by Optimizing Content Information for Maximal Entropy -- Rapid Training Data Generation for Tissue Segmentation Using Global Approximate Block-Matching with Self-Organizing Maps -- Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-slide Images -- Deep semi-supervised segmentation with weight-averaged consistency targets -- Focal Dice Loss and Image Dilation for Brain Tumor Segmentation -- Automatic Detection of Patients with a High Risk of Systolic Cardiac Failure in Echocardiography -- Unsupervised feature learning for outlier detection with stacked convolutional autoencoders, siamese networks and Wasserstein autoencoders: application to epilepsy detection -- Automatic myocardial strain imaging in echocardiography using deep learning -- 3D Convolutional Neural Networks for Classification of Functional Connectomes -- Computed Tomography Image Enhancement using 3D Convolutional Neural Network -- Deep Particle Tracker: Automatic Tracking of Particles in Fluorescence Microscopy Images Using Deep Learning -- A Unified Framework Integrating Recurrent Fully-convolutional Networks and Optical Flow for Segmentation of the Left Ventricle in Echocardiography Data -- Learning Optimal Deep Proje…
  note: edited by Danail Stoyanov, Zeike Taylor, Gustavo Carneiro, Tanveer Syeda-Mahmood, Anne Martel, Lena Maier-Hein, Joao Manuel R.S. Tavares, Andrew Bradley, Joao Paulo Papa, Vasileios Belagiannis, Jacinto C. Nascimento, Zhi Lu, Sailesh Conjeti, Mehdi Moradi, Hayit Greenspan, Anant Madabhushi.
  note: Electronic resource.
  subject:
    topic: Artificial intelligence
  subject:
    topic: Medical records
    topic: Data processing
  subject:
    topic: Education
  subject:
    topic: Social sciences
    topic: Data processing
  subject:
    topic: Computer security
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Health Informatics
  subject:
    topic: Computers and Education
  subject:
    topic: Computer Appl. in Social and Behavioral Sciences
  subject:
    topic: Systems and Data Security
  classification: Q334-342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: LNCS sublibrary. 11045
      part number: SL 6
      part name: Image processing, computer vision, pattern recognition, and graphics
  identifier: 9783030008895
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 180919
    record change date: 20240730205425.0
    record identifier: in00004014283