deploy: 853bd7c

Author: anjos

cv.pdf

@@ -36,11 +36,82 @@ @article{acmhealth-2026
   infrastructure and computational resources.},
 }
 
+@article{scirep-2026,
+  author = {Amiot, Victor and Pulvirenti, Roberto and
+    Jimenez-del-Toro, Oscar and Ott, Muriel and Bogaciu,
+    Teodora-Elena and Banerjee, Shalini and Amstutz, Christoph and
+    Odobez, Jean-Marc and Chiquet, Christophe and Guex-Crosier, Yan
+    and Bergin, Ciara and Meloni, Ilenia and Anjos, Andr{\'{e}} and
+  Hoogewoud, Florence and Tomasoni, Mattia},
+  keywords = {Clinical translation, deep learning, disease grading,
+  fluorescein angiography, inter-grader agreement, Uveitis, vasculitis},
+  month = may,
+  title = {UveAI: clinic-ready scoring of retinal inflammation in
+  uveitis on widefield fluorescein angiography using AI},
+  journal = {Scientific reports},
+  year = {2026},
+  url = {https://www.nature.com/articles/s41598-026-46069-w},
+  doi = {10.1038/s41598-026-46069-w},
+  abstract = {Retinal inflammation is a key determinant of visual
+    prognosis in uveitis, yet its assessment on fluorescein
+    angiography remains subjective, labor-intensive, and
+    insufficiently scalable for clinical trials or large cohort
+    studies. Fluorescein angiography is the gold standard for
+    assessing retinal inflammation. However, its scoring remains
+    challenging, as the process is complex and time-consuming,
+    limiting routine use in clinical trials and patient care. We
+    present UveAI, a modular deep learning framework that grades all
+    major retinal inflammatory signs in fluorescein angiography
+    across posterior pole and periphery to generate an ASUWOG-aligned
+    inflammation score. Trained on 3,220 FA images from 644 eyes (369
+    patients), UveAI integrates six transformer models detecting
+    macular edema, optic disc hyperfluorescence, and vascular and
+    capillary leakage in the posterior pole and periphery. On an
+    independent test set, UveAI showed high concordance with an
+    expert grader for total score (R = 0.96) and strong performance
+    for individual signs (mean AUC = 0.952). Grad-CAM maps confirmed
+    clinically relevant focus, supporting automated, standardised FA
+  scoring in uveitis.}
+}
+
+@inproceedings{isbi-2026,
+  author = {Pulvirenti, Roberto and Jimenez-del-Toro, Oscar and
+    Tomasoni, Mattia and
+  Hoogewoud, Florence and Anjos, Andr{\'{e}}},
+  title = {When Specialization Helps (and Hurts): Cross-Modality
+  Transfer in Ophthalmic Imaging with Foundation Models},
+  booktitle = {2026 IEEE 23rd International Symposium on Biomedical Imaging},
+  year = {2026},
+  url = {https://www.idiap.ch/paper/retinal-fm-specialization/},
+  doi = {10.1109/ISBI61048.2026.11515636},
+  abstract = {Large publicly available datasets for specialized
+    medical imaging are rare, limiting model development and
+    motivating knowledge transfer from related, data-rich modalities.
+    We explore this in ophthalmology by investigating whether retinal
+    foundation models (FMs) pretrained on Color Fundus Photographs
+    (CFP) transfer more effectively to other ophthalmic modalities,
+    specifically Fluorescein Angiography (FA) and Indocyanine Green
+    Angiography (ICGA), than nonspecialist FMs trained on natural
+    images. In particular, we examine how the Self-Supervised
+    Learning (SSL) strategy and model size influence this transfer.
+    Using the public AngioReport dataset, six FMs were fine-tuned on
+    three angiography tasks and thoroughly evaluated. Attention-based
+    analyses, performed both quantitatively and qualitatively,
+    further contextualized the results. Our experiments show that
+    cross-modality transfer in retinal FMs is critically dependent on
+    the SSL method applied during the pretraining phase: while DINOv2
+    and Token-Reconstruction objectives preserve diverse
+    representations that generalize well across modalities, MAE
+    pretraining leads to overspecialization, a narrowing of
+    representations that limits transferability to other retinal
+  imaging domains.}
+}
+
 %%%%%%%%%%%%
 %%  2025  %%
 %%%%%%%%%%%%
 
-@ARTICLE{melba-2025,
+@article{melba-2025,
   author = {{\"{O}}zbulak, G{\"{o}}khan and Jimenez-del-Toro, Oscar
   and Fatoretto, Ma{\'{\i}}ra and Berton, Lilian and Anjos, Andr{\'{e}}},
   keywords = {machine learning, Medical Image Analysis,
@@ -240,7 +311,8 @@ @inproceedings{aime-2025
   month = 6,
   title = {STM-GNN: Space-Time-and-Memory Graph Neural Networks for
   Predicting Multi-Drug Resistance Risks in Dynamic Patient Networks},
-  booktitle = {International Conference on Artificial Intelligence in Medicine},
+  booktitle = {International Conference on Artificial Intelligence
+  in Medicine},
   year = {2025},
   location = {Pavia, Italy},
   isbn = {978-3-031-95838-0},
@@ -297,14 +369,16 @@ @misc{ssrn-2024
 }
 
 @inproceedings{miccai-2024,
-  author = {Queiroz Neto, Dilermando and Anjos, Andr{\'{e}} and Berton, Lilian},
+  author = {Queiroz Neto, Dilermando and Anjos, Andr{\'{e}} and
+  Berton, Lilian},
   keywords = {Fairness, Foundation Model, Medical Image},
   month = 10,
   title = {Using Backbone Foundation Model for Evaluating Fairness in
   Chest Radiography Without Demographic Data},
   booktitle = {Proceedings of the International Conference on Medical
   Image Computing and Computer Assisted Intervention (MICCAI)},
   year = {2024},
+  doi = {10.1007/978-3-031-72787-0_11},
   abstract = {Ensuring consistent performance across diverse
     populations and incorporating fairness into machine learning models
     are crucial for advancing medical image diagnostics and promoting
@@ -343,6 +417,7 @@ @inproceedings{eccv-2024
   booktitle = {Proceedings of the 18th European Conference on
   Computer Vision (ECCV)},
   year = {2024},
+  doi = {10.48550/arXiv.2408.16154},
   abstract = {Foundation models have emerged as robust models with
     label efficiency in diverse domains. In medical imaging, these
     models contribute to the advancement of medical diagnoses due to
@@ -377,6 +452,7 @@ @inproceedings{euvip-2024-2
   booktitle = {Proceedings of the 12th European Workshop on Visual
   Information Processing},
   year = {2024},
+  doi = {10.1109/EUVIP61797.2024.10772813},
   abstract = {Radiomics have the ability to comprehensively quantify
     human tissue characteristics in medical imaging studies. However,
     standard radiomic features are highly unstable due to their
@@ -408,6 +484,7 @@ @inproceedings{euvip-2024-1
   booktitle = {Proceedings of the 12th European Workshop on Visual
   Information Processing},
   year = {2024},
+  doi = {10.1109/EUVIP61797.2024.10772829},
   abstract = {Automatic classification of active tuberculosis from
     chest X-ray images has the potential to save lives, especially in
     low- and mid-income countries where skilled human experts can be
@@ -445,35 +522,50 @@ @article{mvr-2024
   issn = {0026-2862},
   doi = {10.1016/j.mvr.2023.104648},
   abstract = {Purpose: To measure non-invasively retinal venous blood flow
-    (RBF) in healthy subjects and patients with retinal venous occlusion (RVO).
+    (RBF) in healthy subjects and patients with retinal venous
+    occlusion (RVO).
 
     Methods: The prototype named AO-LDV (Adaptive Optics Laser Doppler
-    Velocimeter), which combines a new absolute laser Doppler velocimeter with
+    Velocimeter), which combines a new absolute laser Doppler
+    velocimeter with
     an adaptive optics fundus camera (rtx1, Imagine Eyes{\textregistered},
     Orsay, France), was studied for the measurement of absolute RBF as a
     function of retinal vessel diameters and simultaneous measurement of red
     blood cell velocity. RBF was measured in healthy subjects (n = 15) and
-    patients with retinal venous occlusion (RVO, n = 6). We also evaluated two
+    patients with retinal venous occlusion (RVO, n = 6). We also
+    evaluated two
     softwares for the measurement of retinal vessel diameters: software 1
-    (automatic vessel detection, profile analysis) and software 2 (based on the
-      use of deep neural networks for semantic segmentation of vessels, using a
+    (automatic vessel detection, profile analysis) and software 2
+    (based on the
+      use of deep neural networks for semantic segmentation of
+      vessels, using a
     M2u-Net architecture).
 
     Results: Software 2 provided a higher rate of automatic retinal vessel
     measurement (99.5 \% of 12,320 AO images) than software 1 (64.9 \%) and
     wider measurements (75.5 ± 15.7 μm vs 70.9 ± 19.8 μm, p < 0.001). For
-    healthy subjects (n = 15), all the retinal veins in one eye were measured
-    to obtain the total RBF. In healthy subjects, the total RBF was 37.8 ± 6.8
-    μl/min. There was a significant linear correlation between retinal vessel
-    diameter and maximal velocity (slope = 0.1016; p < 0.001; r2 = 0.8597) and
-    a significant power curve correlation between retinal vessel diameter and
+    healthy subjects (n = 15), all the retinal veins in one eye
+    were measured
+    to obtain the total RBF. In healthy subjects, the total RBF
+    was 37.8 ± 6.8
+    μl/min. There was a significant linear correlation between
+    retinal vessel
+    diameter and maximal velocity (slope = 0.1016; p < 0.001; r2
+    = 0.8597) and
+    a significant power curve correlation between retinal vessel
+    diameter and
     blood flow (3.63 × 10−5 × D2.54; p < 0.001; r2 = 0.7287). No significant
-    relationship was found between total RBF and systolic and diastolic blood
+    relationship was found between total RBF and systolic and
+    diastolic blood
     pressure, ocular perfusion pressure, heart rate, or hematocrit. For RVO
-    patients (n = 6), a significant decrease in RBF was noted in occluded veins
-    (3.51 ± 2.25 μl/min) compared with the contralateral healthy eye (11.07 ±
-    4.53 μl/min). For occluded vessels, the slope between diameter and velocity
-    was 0.0195 (p < 0.001; r2 = 0.6068) and the relation between diameter and
+    patients (n = 6), a significant decrease in RBF was noted in
+    occluded veins
+    (3.51 ± 2.25 μl/min) compared with the contralateral healthy
+    eye (11.07 ±
+    4.53 μl/min). For occluded vessels, the slope between
+    diameter and velocity
+    was 0.0195 (p < 0.001; r2 = 0.6068) and the relation between
+    diameter and
     flow was Q = 9.91 × 10−6 × D2.41 (p < 0.01; r2 = 0.2526).
 
     Conclusion: This AO-LDV prototype offers new opportunity to study
@@ -490,7 +582,8 @@ @inproceedings{cbms-2023
     Pauline AND Guex-Crosier, Yan AND Bergin, Ciara AND Anjos, André
   AND Hoogewoud, Florence AND Tomasoni, Mattia},
   title = {Fully Automatic Grading of Retinal Vasculitis on
-  Fluorescein Angiography Time-lapse from Real-world Data in Clinical Settings},
+    Fluorescein Angiography Time-lapse from Real-world Data in
+  Clinical Settings},
   booktitle={2023 IEEE 36th International Symposium on Computer-Based
   Medical Systems (CBMS)},
   year = {2023},
@@ -738,10 +831,12 @@ @inproceedings{cbic-2021
     surrounded by other lung pixels.
 
     This work is reproducible.  Source code, evaluation protocols and
-  baseline results are available at: https://pypi.org/project/bob.ip.binseg/.},
+    baseline results are available at:
+  https://pypi.org/project/bob.ip.binseg/.},
   eventtitle = {Congresso Brasileiro de Inteligência Computacional},
   pages = {1--8},
-  booktitle = {Anais do 15. Congresso Brasileiro de Inteligência Computacional},
+  booktitle = {Anais do 15. Congresso Brasileiro de Inteligência
+  Computacional},
   year = {2021},
   month = 10,
   publisher = {{SBIC}},
@@ -913,7 +1008,8 @@ @patent{3dfv-patent-2019
 
 @article{tifs-2019-2,
   author = {George, Anjith and Mostaani, Zohreh and Geissenbuhler,
-  David and Nikisins, Olegs and Anjos, Andr{\'{e}} and Marcel, S{\'{e}}bastien},
+    David and Nikisins, Olegs and Anjos, Andr{\'{e}} and Marcel,
+  S{\'{e}}bastien},
   title = {Biometric Face Presentation Attack Detection with
   Multi-Channel Convolutional Neural Network},
   journal = {IEEE Transactions on Information Forensics and Security},
@@ -1161,7 +1257,8 @@ @inproceedings{icb-2018
   month = 2,
   title = "On Effectiveness of Anomaly Detection Approaches against
   Unseen Presentation Attacks in Face Anti-Spoofing",
-  booktitle = "The 11th IAPR International Conference on Biometrics (ICB 2018)",
+  booktitle = "The 11th IAPR International Conference on Biometrics
+  (ICB 2018)",
   year = "2018",
   url = "https://publications.idiap.ch/index.php/publications/show/3793",
   pdf = "https://www.idiap.ch/~aanjos/papers/icb-2018.pdf",
@@ -1671,7 +1768,8 @@ @article{eurasip-2014
 
 @article{iet-biometrics-2013,
   author = "André Anjos AND Murali Mohan Chakka AND Sébastien Marcel",
-  title = "Motion-Based Counter-Measures to Photo Attacks in Face Recognition",
+  title = "Motion-Based Counter-Measures to Photo Attacks in Face
+  Recognition",
   journal = "IET Biometrics",
   year = "2013",
   month = 7,
@@ -1701,7 +1799,8 @@ @article{iet-biometrics-2013
 
 @inproceedings{cvpr-bw-2013,
   author = "Ivana Chingovska AND André Anjos AND Sébastien Marcel",
-  title = "Anti-spoofing in action: joint operation with a verification system",
+  title = "Anti-spoofing in action: joint operation with a
+  verification system",
   booktitle = "Computer Vision and Pattern Recognition Conference -
   Biometrics Workshop",
   year = "2013",
@@ -1794,7 +1893,8 @@ @inproceedings{icb-2013-3
   Gabbouj AND R. Tronci AND M. Pili AND N. Sirena AND F. Roli AND J.
   Galbally AND J. Fierrez AND A. Pinto AND H. Pedrini AND W. S.
   Schwartz AND A. Rocha AND A. Anjos AND S. Marcel",
-  title = "The 2nd Competition on Counter Measures to 2D Face Spoofing Attacks",
+  title = "The 2nd Competition on Counter Measures to 2D Face
+  Spoofing Attacks",
   booktitle = "International Conference on Biometrics 2013",
   month = 6,
   year = "2013",
@@ -1867,7 +1967,8 @@ @inproceedings{acmmm-2012
 
 @inproceedings{biosig-2012,
   author = "Ivana Chingovska AND André Anjos AND Sébastien Marcel",
-  title = "On the Effectiveness of Local Binary Patterns in Face Anti-spoofing",
+  title = "On the Effectiveness of Local Binary Patterns in Face
+  Anti-spoofing",
   booktitle = "IEEE International Conference of the Biometrics
   Special Interest Group",
   year = "2012",
@@ -1973,7 +2074,8 @@ @article{cpc-2009
 
 @inproceedings{nima-2010,
   author = "The ATLAS Collaboration",
-  title = "ATLAS Trigger and Data Acquisition: capabilities and commissioning",
+  title = "ATLAS Trigger and Data Acquisition: capabilities and
+  commissioning",
   year = "2010",
   volume = "617",
   number = "1",
@@ -2069,7 +2171,8 @@ @inproceedings{chep-2009
 
 @inproceedings{tipp-2009,
   author = "The ATLAS Collaboration",
-  title = "Configuration and Control of the ATLAS Trigger and Data Acquisition",
+  title = "Configuration and Control of the ATLAS Trigger and Data
+  Acquisition",
   booktitle = "The 1st international conference on Technology and
   Instrumentation in Particle Physics",
   year = "2009",
@@ -2461,7 +2564,8 @@ @inproceedings{rt-2007-3
   readout buffers containing the events, event building, second level
   and third level trigger algorithms. Quantities critical for the
   final system, such as event processing times, have been studied
-  using different trigger algorithms as well as different dataflow components.",
+  using different trigger algorithms as well as different dataflow
+  components.",
 }
 
 @inproceedings{rt-2007-2,
@@ -2528,7 +2632,8 @@ @inproceedings{rt-2007
 
 @phdthesis{phd-thesis-2006,
   author = "André Anjos",
-  title = "Sistema Online de Filtragem em um Ambiente com Alta Taxa de Eventos",
+  title = "Sistema Online de Filtragem em um Ambiente com Alta Taxa
+  de Eventos",
   school = "COPPE/UFRJ",
   year = "2006",
   pdf = "https://www.idiap.ch/~aanjos/papers/phd-thesis-2006.zip",
@@ -2553,7 +2658,8 @@ @phdthesis{phd-thesis-2006
 
 @article{nimb-2006,
   author = "The ATLAS Collaboration",
-  title = "The ATLAS Data Acquisition and Trigger : concept, design and status",
+  title = "The ATLAS Data Acquisition and Trigger : concept, design
+  and status",
   journal = "Nucl. Phys. B, Proc. Suppl.",
   year = "2006",
   month = 11,
@@ -3304,7 +3410,8 @@ @article{ieee-tns-2004
 
 @inproceedings{astro-2003,
   author = "The ATLAS Collaboration",
-  title = "Architecture of the ATLAS online physics-selection software at LHC",
+  title = "Architecture of the ATLAS online physics-selection
+  software at LHC",
   booktitle = "Conference on Astroparticle, Particle, Space Physics,
   Detectors and Medical Physics Applications",
   year = "2003",