Computational Pathology and Ophthalmic Medical Image Analysis

​Improving Accuracy of Nuclei Segmentation by Reducing Histological Image Variability.- Multi-Resolution Networks for Semantic Segmentation in Whole Slide Images.- Improving High Resolution Histology Image Classification with Deep Spatial Fusion Network.- Construction of a Generative Model of H&E Stained Pathology Images of Pancreas Tumors Conditioned by a Voxel Value of MRI Image.- Accurate 3D reconstruction of a whole pancreatic cancer tumor from pathology images with different stains.- Role of Task Complexity and Training in Crowdsourced Image Annotation.- Capturing global spatial context for accurate cell classification in skin cancer histology.- Exploiting Multiple Color Representations to Improve Colon Cancer Detection in Whole Slide H&E Stains.- Leveraging Unlabeled Whole-Slide-Images for Mitosis Detection.- Evaluating Out-of-the-box Methods for the Classification of Hematopoietic Cells in Images of Stained Bone Marrow.- DeepCerv: Deep neural network for segmentation free robust cervical cell classification.- Whole slide image registration for the study of tumor heterogeneity.- Modality Conversion from Pathological Image to Ultrasonic Image Using Convolutional Neural Network.- Structure instance segmentation in renal tissue: a case study on tubular immune cell detection.- Cellular Community Detection for Tissue Phenotyping in Histology Images.- Automatic Detection of Tumor Budding in Colorectal Carcinoma with Deep Learning.- Significance of Hyperparameter Optimization for Metastasis Detection in Breast Histology Images.- Image Magnification Regression Using DenseNet for Exploiting Histopathology Open Access Content.- Uncertainty Driven Pooling Network for Microvessel Segmentation in Routine Histology Images.- Ocular Structures Segmentation from Multi-sequences MRI using 3D Unet with Fully Connected CRFs.- Classification of Findings with Localized Lesions in Fundoscopic Images using a Regionally Guided CNN.- Segmentation of Corneal Nerves Using a U-Net-based Convolutional Neural Network.- Automatic Pigmentation Grading of the Trabecular Meshwork in Gonioscopic Images.- Large Receptive Field Fully Convolutional Network for Semantic Segmentation of Retinal Vasculature in Fundus Images.- Explaining Convolutional Neural Networks for Area Estimation of Choroidal Neovascularization via Genetic Programming.- Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images using Bayesian Deep Learning.- cGAN-based lacquer cracks segmentation in ICGA image.- Localizing Optic Disc and Cup for Glaucoma Screening via Deep Object Detection Networks.- Fundus Image Quality-guided Diabetic Retinopathy Grading.- DeepDisc: Optic Disc Segmentation based on Atrous Convolution and Spatial Pyramid Pooling.- Large-scale Left and Right Eye Classification in Retinal Images.- Automatic Segmentation of Cortex and Nucleus in Anterior Segment OCT Images.- Local Estimation of the Degree of Optic Disc Swelling from Color Fundus Photography.- Visual Field based Automatic Diagnosis of Glaucoma Using Deep Convolutional Neural Network.- Towards standardization of retinal vascular measurements: on the effect of image centering.- Feasibility study of Subfoveal Choroidal Thickness Changes in Spectral-Domain Optical Coherence Tomography Measurements of Macular Telangiectasia Type 2.- Segmentation of retinal layers in OCT images of the mouse eye utilizing polarization contrast.- Glaucoma Diagnosis from Eye Fundus Images Based on Deep Morphometric Feature Estimation.- 2D Modeling and Correction of Fan-beam Scan Geometry in OCT.- A Bottom-up Saliency Estimation Approach for Neonatal Retinal Images.<div><br></div>