Titlebook: Ophthalmic Medical Image Analysis; 6th International Wo Huazhu Fu,Mona K. Garvin,Yalin Zheng Conference proceedings 2019 Springer Nature Sw

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0302-9743 019...The 22 full papers (out of 36 submissions) presented at OMIA 2019 were carefully reviewed and selected. The papers cover various topics in the field of ophthalmic image analysis..978-3-030-32955-6978-3-030-32956-3Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Region-Based Segmentation of Capillary Density in Optical Coherence Tomography Angiography,n of each of the following categories: avascular, hypovascular, and capillary-dense. The AUCs (area under the receiver operating characteristic curves) were 0.99 (avascular), 0.93 (hypovascular), and 0.97 (capillary-dense) for segmenting each of the categories. The results show very good performance

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Foveal Avascular Zone Segmentation in Clinical Routine Fluorescein Angiographies Using Multitask Lets an additional Euclidean distance map prediction task to better deal with variable imaging conditions, by benefiting from its regularization effect. Our method is empirically evaluated using a data set of FA scans from large multicenter clinical trials with diverse qualities and image resolutions.

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Shape Decomposition of Foveal Pit Morphology Using Scan Geometry Corrected OCT,n current literature. Lastly, we evaluated the relationship between the first principal mode of variation in the cohort and the axial length from each subject. Our findings showed a modest inverse relationship between axial length and foveal pit depth that can be confirmed independently by existing

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Deriving Visual Cues from Deep Learning to Achieve Subpixel Cell Segmentation in Adaptive Optics Reentroid and region distribution information as a means for facilitating cell segmentation. Five-color theorem guarantees the separation of any touching cells. Finally, a region-based level set algorithm that combines all of these visual cues is used to achieve subpixel cell segmentation. Five-fold c

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Fundus Image Based Retinal Vessel Segmentation Utilizing a Fast and Accurate Fully Convolutional Nealuate the proposed approach both quantitatively and qualitatively. The proposed method was found to exhibit superior performance, with the average areas under the ROC curve being 0.9826 and 0.9865 and the average accuracies being 0.9579 and 0.9664 for the aforementioned two datasets, which outperfo

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Encoder-Decoder Attention Network for Lesion Segmentation of Diabetic Retinopathy,rrelation information of the same stage feature and pay more attention to lesion areas. In order to capture large receptive fields and accurately segment small lesion, the modified lightweight residual network with dilated convolution is employed in encoding path. Besides, a hybrid loss, consisting