Table of Contents

• Improving Accuracy of Nuclei Segmentation by Reducing Histological Image VariabilityYusuf H. Roohani, Eric G. Kiss. 3-10 [doi]
• Multi-resolution Networks for Semantic Segmentation in Whole Slide ImagesFeng Gu, Nikolay Burlutskiy, Mats Andersson, Lena Kajland Wilén. 11-18 [doi]
• Improving High Resolution Histology Image Classification with Deep Spatial Fusion NetworkYongxiang Huang, Albert Chi-shing Chung. 19-26 [doi]
• Construction of a Generative Model of H&E Stained Pathology Images of Pancreas Tumors Conditioned by a Voxel Value of MRI ImageTomoshige Shimomura, Mauricio Kugler, Tatsuya Yokota, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume, Hidekata Hontani. 27-34 [doi]
• Accurate 3D Reconstruction of a Whole Pancreatic Cancer Tumor from Pathology Images with Different StainsMauricio Kugler, Yushi Goto, Naoki Kawamura, Hirokazu Kobayashi, Tatsuya Yokota, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume, Hidekata Hontani. 35-43 [doi]
• Role of Task Complexity and Training in Crowdsourced Image AnnotationNadine S. Schaadt, Anne Grote, Germain Forestier, Cédric Wemmert, Friedrich Feuerhake. 44-51 [doi]
• Capturing Global Spatial Context for Accurate Cell Classification in Skin Cancer HistologyKonstantinos Zormpas-Petridis, Henrik Failmezger, Ioannis Roxanis, Matthew D. Blackledge, Yann Jamin, Yinyin Yuan. 52-60 [doi]
• Exploiting Multiple Color Representations to Improve Colon Cancer Detection in Whole Slide H&E StainsAlex Skovsbo Jørgensen, Jonas Emborg, Rasmus Røge, Lasse Riis Østergaard. 61-68 [doi]
• Leveraging Unlabeled Whole-Slide-Images for Mitosis DetectionSaad Ullah Akram, Talha Qaiser, Simon Graham, Juho Kannala, Janne Heikkilä, Nasir M. Rajpoot. 69-77 [doi]
• Evaluating Out-of-the-Box Methods for the Classification of Hematopoietic Cells in Images of Stained Bone MarrowPhilipp Gräbel, Martina Crysandt, Reinhild Herwartz, Melanie Hoffmann, Barbara Mara Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof. 78-85 [doi]
• DeepCerv: Deep Neural Network for Segmentation Free Robust Cervical Cell ClassificationO. U. Nirmal Jith, K. K. Harinarayanan, Srishti Gautam, Arnav Bhavsar, Anil Kumar Sao. 86-94 [doi]
• Whole Slide Image Registration for the Study of Tumor HeterogeneityLeslie Solorzano, Gabriela M. Almeida, Bárbara Mesquita, Diana Martins, Carla Oliveira, Carolina Wählby. 95-102 [doi]
• Modality Conversion from Pathological Image to Ultrasonic Image Using Convolutional Neural NetworkTakashi Ohnishi, Shu Kashio, Takuya Ogawa, Kazuyo Ito, Stanislav S. Makhanov, Tadashi Yamaguchi, Yasuo Iwadate, Hideaki Haneishi. 103-111 [doi]
• Structure Instance Segmentation in Renal Tissue: A Case Study on Tubular Immune Cell DetectionThomas de Bel, Meyke Hermsen, Geert J. S. Litjens, Jeroen van der Laak. 112-119 [doi]
• Cellular Community Detection for Tissue Phenotyping in Histology ImagesSajid Javed, Muhammad Moazam Fraz, David B. A. Epstein, David R. J. Snead, Nasir M. Rajpoot. 120-129 [doi]
• Automatic Detection of Tumor Budding in Colorectal Carcinoma with Deep LearningJohn-Melle Bokhorst, Lucia Rijstenberg, Danny Goudkade, Iris Nagtegaal, Jeroen van der Laak, Francesco Ciompi. 130-138 [doi]
• Significance of Hyperparameter Optimization for Metastasis Detection in Breast Histology ImagesNavid Alemi Koohbanani, Talha Qaiser, Muhammad Shaban, Jevgenij Gamper, Nasir M. Rajpoot. 139-147 [doi]
• Image Magnification Regression Using DenseNet for Exploiting Histopathology Open Access ContentSebastian Otálora, Manfredo Atzori, Vincent Andrearczyk, Henning Müller. 148-155 [doi]
• Uncertainty Driven Pooling Network for Microvessel Segmentation in Routine Histology ImagesM. M. Fraz, Muhammad Shaban, Simon Graham, Syed Ali Khurram, Nasir M. Rajpoot. 156-164 [doi]
• Ocular Structures Segmentation from Multi-sequences MRI Using 3D Unet with Fully Connected CRFsHuu-Giao Nguyen, Alessia Pica, Philippe Maeder, Ann Schalenbourg, Marta Peroni, Jan Hrbacek, Damien C. Weber, Meritxell Bach Cuadra, Raphael Sznitman. 167-175 [doi]
• Classification of Findings with Localized Lesions in Fundoscopic Images Using a Regionally Guided CNNJaemin Son, Woong Bae, Sangkeun Kim, Sang-Jun Park, Kyu-Hwan Jung. 176-184 [doi]
• Segmentation of Corneal Nerves Using a U-Net-Based Convolutional Neural NetworkAlessia Colonna, Fabio Scarpa, Alfredo Ruggeri. 185-192 [doi]
• Automatic Pigmentation Grading of the Trabecular Meshwork in Gonioscopic ImagesAndrea De Giusti, Simone Pajaro, Masaki Tanito. 193-200 [doi]
• Large Receptive Field Fully Convolutional Network for Semantic Segmentation of Retinal Vasculature in Fundus ImagesGabriel Lepetit-Aimon, Renaud Duval, Farida Cheriet. 201-209 [doi]
• Explaining Convolutional Neural Networks for Area Estimation of Choroidal Neovascularization via Genetic ProgrammingYibiao Rong, Kai Yu, Dehui Xiang, Weifang Zhu, Zhun Fan, Xinjian Chen. 210-218 [doi]
• Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images Using Bayesian Deep LearningSuman Sedai, Bhavna J. Antony, Dwarikanath Mahapatra, Rahil Garnavi. 219-227 [doi]
• cGAN-Based Lacquer Cracks Segmentation in ICGA ImageHongjiu Jiang, Yuhui Ma, Weifang Zhu, Ying Fan, Yihong Hua, Qiuying Chen, Xinjian Chen. 228-235 [doi]
• Localizing Optic Disc and Cup for Glaucoma Screening via Deep Object Detection NetworksXu Sun, Yanwu Xu, Mingkui Tan, Huazhu Fu, Wei Zhao, Tianyuan You, Jiang Liu. 236-244 [doi]
• Fundus Image Quality-Guided Diabetic Retinopathy GradingKang Zhou, Zaiwang Gu, Annan Li, Jun Cheng, Shenghua Gao, Jiang Liu. 245-252 [doi]
• DeepDisc: Optic Disc Segmentation Based on Atrous Convolution and Spatial Pyramid PoolingZaiwang Gu, Peng Liu, Kang Zhou, Yuming Jiang, Haoyu Mao, Jun Cheng, Jiang Liu. 253-260 [doi]
• Large-Scale Left and Right Eye Classification in Retinal ImagesPeng Liu, Zaiwang Gu, Fan Liu, Yuming Jiang, Shanshan Jiang, Haoyu Mao, Jun Cheng, Lixin Duan, Jiang Liu. 261-268 [doi]
• Automatic Segmentation of Cortex and Nucleus in Anterior Segment OCT ImagesPengshuai Yin, Mingkui Tan, HuaQing Min, Yanwu Xu, Guanghui Xu, Qingyao Wu, Yunfei Tong, Higashita Risa, Jiang Liu. 269-276 [doi]
• Local Estimation of the Degree of Optic Disc Swelling from Color Fundus PhotographySamuel S. Johnson, Jui-Kai Wang, Mohammad Shafkat Islam, Matthew J. Thurtell, Randy H. Kardon, Mona Kathryn Garvin. 277-284 [doi]
• Visual Field Based Automatic Diagnosis of Glaucoma Using Deep Convolutional Neural NetworkFei Li, Zhe Wang, Guoxiang Qu, Yu Qiao, Xiulan Zhang. 285-293 [doi]
• Towards Standardization of Retinal Vascular Measurements: On the Effect of Image CenteringMuthu Rama Krishnan Mookiah, Sarah McGrory, Stephen Hogg, Jackie Price, Rachel Forster, Thomas J. MacGillivray, Emanuele Trucco. 294-302 [doi]
• Feasibility Study of Subfoveal Choroidal Thickness Changes in Spectral-Domain Optical Coherence Tomography Measurements of Macular Telangiectasia Type 2Tiziano Ronchetti, Peter Maloca, Emanuel Ramos de Carvalho, Tjebo F. C. Heeren, Konstantinos Balaskas, Adnan Tufail, Catherine Egan, Mali Okada, Selim Orgül, Christoph Jud, Philippe C. Cattin. 303-309 [doi]
• Segmentation of Retinal Layers in OCT Images of the Mouse Eye Utilizing Polarization ContrastMarco Augustin, Danielle J. Harper, Conrad W. Merkle, Christoph K. Hitzenberger, Bernhard Baumann. 310-318 [doi]
• Glaucoma Diagnosis from Eye Fundus Images Based on Deep Morphometric Feature EstimationOscar Perdomo, Vincent Andrearczyk, Fabrice Mériaudeau, Henning Müller, Fabio A. González. 319-327 [doi]
• 2D Modeling and Correction of Fan-Beam Scan Geometry in OCTMin Chen, James C. Gee, Jerry L. Prince, Geoffrey K. Aguirre. 328-335 [doi]
• A Bottom-Up Saliency Estimation Approach for Neonatal Retinal ImagesSharath M. Shankaranarayana, Keerthi Ram, Anand Vinekar, Kaushik Mitra, Mohanasankar Sivaprakasam. 336-343 [doi]