Medical Image Understanding and Analysis

1. Front Matter

   Pages I-XIX

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2. Retinal Imaging

   1. Front Matter

      Pages 1-1

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   2. End-to-End Learning of a Conditional Random Field for Intra-retinal Layer Segmentation in Optical Coherence Tomography

      • Arunava Chakravarty, Jayanthi Sivaswamy

      Pages 3-14

   3. Superpixel-Based Line Operator for Retinal Blood Vessel Segmentation

      • Tong Na, Yitian Zhao, Yifan Zhao, Yue Liu

      Pages 15-26

   4. Automatic Detection and Identification of Retinal Vessel Junctions in Colour Fundus Photography

      • Harry Pratt, Bryan M. Williams, Jae Ku, Frans Coenen, Yalin Zheng

      Pages 27-37

   5. Fast Optic Disc Segmentation in Retinal Images Using Polar Transform

      • Muhammad Nauman Zahoor, Muhammad Moazam Fraz

      Pages 38-49

   6. A Novel Technique for Splat Generation and Patch Level Prediction in Diabetic Retinopathy

      • I. Syed Muhammedh Ajwahir, Kumar Rajamani, S. Ibrahim Sadhar

      Pages 50-59

3. Ultrasound Imaging

   1. Front Matter

      Pages 61-61

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   2. Deep Residual Networks for Quantification of Muscle Fiber Orientation and Curvature from Ultrasound Images

      • Ryan Cunningham, Peter Harding, Ian Loram

      Pages 63-73

   3. Modelling, Speckle Simulation and Quality Evaluation of Synthetic Ultrasound Images

      • Prerna Singh, Ramakrishnan Mukundan, Rex de Ryke

      Pages 74-85

   4. Multi-level Trainable Segmentation for Measuring Gestational and Yolk Sacs from Ultrasound Images

      • Dheyaa Ahmed Ibrahim, Hisham Al-Assam, Sabah Jassim, Hongbo Du

      Pages 86-97

   5. Weakly Supervised Learning of Placental Ultrasound Images with Residual Networks

      • Huan Qi, Sally Collins, Alison Noble

      Pages 98-108

   6. Edge Aware Geometric Filter for Ultrasound Image Enhancement

      • Deepak Mishra, Santanu Chaudhury, Mukul Sarkar, Arvinder Singh Soin

      Pages 109-120

4. Cardiovascular Imaging

   1. Front Matter

      Pages 121-121

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   2. Tissues Classification of the Cardiovascular System Using Texture Descriptors

      • Claudia Mazo, Enrique Alegre, Maria Trujillo, Víctor González-Castro

      Pages 123-132

   3. Multidimensional Assessments of Abdominal Aortic Aneurysms by Magnetic Resonance Against Ultrasound Diameter Measurements

      • G. Papanastasiou, V. González-Castro, C. D. Gray, R. O. Forsythe, Y. Sourgia-Koutraki, N. Mitchard et al.

      Pages 133-143

   4. Comparison of Automatic Vessel Segmentation Techniques for Whole Body Magnetic Resonance Angiography with Limited Ground Truth Data

      • Andrew McNeil, Giulio Degano, Ian Poole, Graeme Houston, Emanuele Trucco

      Pages 144-155

   5. Evaluating Classifiers for Atherosclerotic Plaque Component Segmentation in MRI

      • Arna van Engelen, Marleen de Bruijne, Torben Schneider, Anouk C. van Dijk, M. Eline Kooi, Jeroen Hendrikse et al.

      Pages 156-168

   6. Cardiac Mesh Reconstruction from Sparse, Heterogeneous Contours

      • Benjamin Villard, Valentina Carapella, Rina Ariga, Vicente Grau, Ernesto Zacur

      Pages 169-181

   7. Classification of Cross-sections for Vascular Skeleton Extraction Using Convolutional Neural Networks

      • Kristína Lidayová, Anindya Gupta, Hans Frimmel, Ida-Maria Sintorn, Ewert Bengtsson, Örjan Smedby

      Pages 182-194

This book constitutes the refereed proceedings of the 21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017, held in Edinburgh, UK, in July 2017.
The 82 revised full papers presented were carefully reviewed and selected from 105 submissions. The papers are organized in topical sections on retinal imaging, ultrasound imaging, cardiovascular imaging, oncology imaging, mammography image analysis, image enhancement and alignment, modeling and segmentation of preclinical, body and histological imaging, feature detection and classification.
The chapters 'Model-Based Correction of Segmentation Errors in Digitised Histological Images' and 'Unsupervised Superpixel-Based Segmentation of Histopathological Images with Consensus Clustering' are open access under a CC BY 4.0 license.

• algorithms
• artificial intelligence
• classification
• Computed Tomography (CT)
• computer aided diagnosis
• convolutional neural networks
• cross-validation
• deep learning
• diagnostic imaging
• digital pathology
• image coding
• image processing
• image reconstruction
• image retrieval
• image segmentation
• machine learning
• neural networks
• Support Vector Machines (SVM)
• ultrasound images

• Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, United Kingdom

  María Valdés Hernández

• University of León, León, Spain

  Víctor González-Castro

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