Vor Ort
Merkzettel Warenkorb
  • Produktbild: Ophthalmic Medical Image Analysis
  • Produktbild: Ophthalmic Medical Image Analysis
Band 11855

Ophthalmic Medical Image Analysis 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, Proceedings

Aus der Reihe Lecture Notes in Computer Science

51,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

18.10.2019

Herausgeber

Huazhu Fu + weitere

Verlag

Springer

Seitenzahl

192

Maße (L/B/H)

23,5/15,5/1,2 cm

Gewicht

318 g

Auflage

1st ed. 2019

Sprache

Englisch

ISBN

978-3-030-32955-6

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

18.10.2019

Herausgeber

Verlag

Springer

Seitenzahl

192

Maße (L/B/H)

23,5/15,5/1,2 cm

Gewicht

318 g

Auflage

1st ed. 2019

Sprache

Englisch

ISBN

978-3-030-32955-6

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)
  • Produktbild: Ophthalmic Medical Image Analysis
  • Produktbild: Ophthalmic Medical Image Analysis

  • Dictionary Learning Informed Deep Neural Network with Application to OCT Images.- Structure-aware Noise Reduction Generative Adversarial Network for Optical Coherence Tomography Image.- Region-Based Segmentation of Capillary Density in Optical Coherence Tomography Angiography.- An amplified-target loss approach for photoreceptor layer segmentation in pathological OCT scans.- Foveal avascular zone segmentation in clinical routine fluorescein angiographies using multitask learning.- Guided M-Net for High-resolution Biomedical Image Segmentation with Weak Boundaries.- 3D-CNN for Glaucoma Detection using Optical Coherence Tomography.- Semi-supervised Adversarial Learning for Diabetic Retinopathy Screening.- Shape Decomposition of Foveal Pit Morphology using Scan Geometry Corrected OCT.- U-Net with spatial pyramid pooling for drusen segmentation in optical coherence tomography.- Deriving Visual Cues from Deep Learning to Achieve Subpixel Cell Segmentation in Adaptive Optics Retinal Images.- Robust Optic Disc Localization by Large Scale Learning.- The Channel Attention based Context Encoder Network for Inner Limiting Membrane Detections.- Fundus Image based Retinal Vessel Segmentation Utilizing A Fast and Accurate Fully Convolutional Network.- Network pruning for OCT image classification.- An improved MPB-CNN segmentation method for edema area and neurosensory retinal detachment in SD-OCT images.- Encoder-Decoder Attention Network for Lesion Segmentation of Diabetic Retinopathy.- Multi-Discriminator Generative Adversarial Networks for improved thin retinal vessel segmentation.- Fovea Localization in Fundus Photographs by Faster R-CNN with Physiological Prior.- Aggressive Posterior Retinopathy of Prematurity Automated Diagnosis via a Deep Convolutional Network.- Automated Stage Analysis of Retinopathy of Prematurity Using Joint Segmentation and Multi-Instance Learning.- Retinopathy Diagnosis using Semi-supervised Multi-channel Generative Adversarial Network.