C-BER - Indexed Articles in Conferences
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ItemDeep Convolutional Artery/Vein Classification of Retinal Vessels( 2018)The classification of retinal vessels into arteries and veins in eye fundus images is a relevant task for the automatic assessment of vascular changes. This paper presents a new approach to solve this problem by means of a Fully-Connected Convolutional Neural Network that is specifically adapted for artery/vein classification. For this, a loss function that focuses only on pixels belonging to the retinal vessel tree is built. The relevance of providing the model with different chromatic components of the source images is also analyzed. The performance of the proposed method is evaluated on the RITE dataset of retinal images, achieving promising results, with an accuracy of 96 % on large caliber vessels, and an overall accuracy of 84 %. © 2018, Springer International Publishing AG, part of Springer Nature.
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ItemAutomatic Characterization of the serous Retinal Detachment Associated with the subretinal Fluid Presence in Optical Coherence Tomography Images( 2018)An accurate detection of the macular edema (ME) presence constitutes a crucial ophthalmological issue as it provides useful information for the identification, diagnosis and treatment of different relevant ocular and Systemic diseaseS. serous Retinal Detachment (sRD) is a particular type of ME, which is characterized by the leakage of fluid that has a propensity of being accumulated in the macular region. This paper proposes a new methodology for the automatic identification and characterization of the sRD edema using Optical Coherence Tomography (OCT) imageS. The subretinal fluids and the External Limiting Membrane (ELM) retinal layers are identified and characterized to measure the disease severity. Four different visualization modules were designed including representative derived parameters to facilitate the doctor's work in the diagnostic evaluation of ME. The different steps of this method were validated using the manual labelling provided by an expert clinician. The validation of the proposed method offered satisfactory results, constituting a suitable scenario with intuitive visual representations that also include different relevant biomarkerS. © 2018 The Author(s).
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