José Ignacio Orlando
José Ignacio Orlando
Assistant Researcher, CONICET
Dirección de correo verificada de - Página principal
TítuloCitado porAño
A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images
JI Orlando, E Prokofyeva, M Blaschko
IEEE Transactions on Biomedical Engineering 64 (1), 16-27, 2017
Learning fully-connected CRFs for blood vessel segmentation in retinal images
JI Orlando, M Blaschko
Medical Image Computing and Computer Assisted Intervention (MICCAI) (2014 …, 2014
An Ensemble Deep Learning Based Approach for Red Lesion Detection in Fundus Images
JI Orlando, E Prokofyeva, M del Fresno, MB Blaschko
Computer Methods and Programs in Biomedicine 153, 115–127, 2017
Convolutional neural network transfer for automated glaucoma identification
JI Orlando, E Prokofyeva, M del Fresno, MB Blaschko
12th International Symposium on Medical Information Processing and Analysis …, 2017
Assessment of image features for vessel wall segmentation in intravascular ultrasound images
L Lo Vercio, JI Orlando, M del Fresno, I Larrabide
International journal of computer assisted radiology and surgery 11 (8 …, 2016
U2-Net: A Bayesian U-Net Model With Epistemic Uncertainty Feedback For Photoreceptor Layer Segmentation In Pathological OCT Scans
JI Orlando, P Seeböck, H Bogunović, S Klimscha, C Grechenig, ...
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019
On Orthogonal Projections for Dimension Reduction and Applications in Augmented Target Loss Functions for Learning Problems
A Breger, JI Orlando, P Harar, M Dörfler, S Klimscha, C Grechenig, ...
arXiv preprint arXiv:1901.07598, 2019
Retinal blood vessel segmentation in high resolution fundus photographs using automated feature parameter estimation
JI Orlando, M Fracchia, V del Río, M del Fresno
13th International Conference on Medical Information Processing and Analysis, 2017
Proliferative Diabetic Retinopathy Characterization based on Fractal Features: Evaluation on a Publicly Available Data Set
JI Orlando, K van Keer, J Barbosa Breda, HL Manterola, MB Blaschko, ...
Medical Physics, 2017
Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT
P Seeböck, JI Orlando, T Schlegl, SM Waldstein, H Bogunović, ...
IEEE Transactions on Medical Imaging 39 (1), 87-98, 2020
Towards a glaucoma risk index based on simulated hemodynamics from fundus images
JI Orlando, JB Breda, K van Keer, MB Blaschko, PJ Blanco, CA Bulant
Medical Image Computing and Computer Assisted Intervention (MICCAI) (2018), 2018
Using CycleGANs for effectively reducing image variability across OCT devices and improving retinal fluid segmentation
P Seeböck, D Romo-Bucheli, S Waldstein, H Bogunović, JI Orlando, ...
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019
Machine learning for ophthalmic screening and diagnostics from fundus images
JI Orlando
Facultad de Ciencias Exactas - Universidad Nacional del Centro de la …, 2017
Un enfoque híbrido para la segmentación de tumores en MRI cerebrales
JI Orlando, E Ferrante, HL Manterola, M del Fresno
3º Congreso Argentino de Informática y Salud, CAIS 2012, 70-91, 2012
SketchZooms: Deep multi-view descriptors for matching line drawings
P Navarro, JI Orlando, C Delrieux, E Iarussi
arXiv preprint arXiv:1912.05019, 2019
REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs
JI Orlando, H Fu, JB Breda, K van Keer, DR Bathula, A Diaz-Pinto, R Fang, ...
Medical image analysis, 101570, 2019
Reviewing Preprocessing and Feature Extraction Techniques for Retinal Blood Vessels Segmentation in Fundus Images
JI Orlando, M del Fresno
Mecánica Computacional 33 (42), 2729-2743, 2014
Reducing image variability across OCT devices with unsupervised unpaired learning for improved segmentation of retina
D Romo-Bucheli, P Seeböck, JI Orlando, BS Gerendas, SM Waldstein, ...
Biomedical Optics Express 11 (1), 346-363, 2020
Foveal Avascular Zone Segmentation in Clinical Routine Fluorescein Angiographies Using Multitask Learning
D Hofer, JI Orlando, P Seeböck, G Mylonas, F Goldbach, A Sadeghipour, ...
International Workshop on Ophthalmic Medical Image Analysis, 35-42, 2019
Linking Function and Structure: Prediction of Retinal Sensitivity in AMD from OCT using Deep Learning
P Seeböck, WD Vogl, SM Waldstein, M Baratsits, JI Orlando, T Alten, ...
Investigative Ophthalmology & Visual Science 60 (9), 1534-1534, 2019
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Artículos 1–20