Image-Based Prediction of Retinal Disease Progression - MICCAI Challenges, DIAMOND 2024 and MARIO 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings

This book constitutes the proceedings from the MICCAI Challenges, Device-Independent Diabetic Macular Edema Onset Prediction, DIAMOND 2024, and Monitoring Age-Related macular degeneration progression in Optical coherence tomography, MARIO 2024, held in conjunction with the 27th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco in October 2024.
The 15 papers included in this book from MARIO 2024 were carefully reviewed and selected from 17 submissions, whereas the 6 papers included here from DIAMOND 2024 were carefully reviewed and selected from 8 submissions. These papers focus on a wide range of state-of-the-art deep learning approaches to derive patient specific rules for Diabetic retinopathy (DR) and age-related macular degeneration (AMD) progression prediction from retinal images.

Dettagli sul prodotto

• Con la collaborazione di: Mostafa El Habib Daho (Editore), Gwenolé Quellec (Editore), Rachid Zeghlache (Editore)
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 15.04.2025
• EAN: 9783031866500
• ISBN: 978-3-0-3186650-0
• Pagine: 224
• Dimensioni: 155 mm x 13 mm x 235 mm
• Peso: 365 g
• Illustrazioni: XI, 224 p. 72 illus., 56 illus. in color.
• Serie: Lecture Notes in Computer Science
• Categorie: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Software applicativo; machine learning, Maschinelles Lernen, Artificial Intelligence, Biomedizinische Technik, Ophthalmology, Diabetic Retinopathy, Computer Imaging, Vision, Pattern Recognition and Graphics, Biomedical Engineering and Bioengineering, life and medical sciences, progression prediction, age-related macular degeneration, retinal image analysis, domain generalization