Update publications

publications.bib

@@ -1,3 +1,33 @@
+%%%%%%%%%%%%
+%%  2023  %%
+%%%%%%%%%%%%
+
+
+@inproceedings{cbms-2023,
+         author = {Amiot, Victor AND Jimenez-del-Toro, Oscar AND Eyraud, 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},
+      booktitle = {Proceedings of the IEEE 36th International Symposium on Computer Based Medical Systems (CBMS) 2023 (to appear)},
+           year = {2023},
+          month = 6,
+       abstract = {The objective of this study is to showcase a pipeline able to perform fully automated grading of retinal inflammation based on a standardised, clinically-validated grading scale. The application of such scale has so far been hindered by the the amount of time required to (manually) apply it in clinical settings. Our dataset includes 3,205 fluorescein angiography images from 148 patients and 242 eyes from the uveitis department of Jules Gonin Eye Hospital. The data was automatically extracted from a medical device, in hospital settings. Images were graded by a medical expert. We focused specifically on one type of inflammation, namely retinal vasculitis. Our pipeline comprises both learning-based models (Pasa model with F1 score = 0.81, AUC = 0.86), and an intensity-based approach to serve as a baseline (F1 score = 0.57, AUC = 0.66). A recall of up to 0.833 computed in an independent test set is comparable to the scores obtained by available state-of-the-art approaches. Here we present the first fully automated pipeline for the grading of retinal vasculitis from raw medical images that is applicable to a real-world clinical data.},
+}
+
+
+@article{ijtld-2023,
+	title = {The rise of artificial intelligence reading of chest X-rays for enhanced TB diagnosis and elimination},
+	doi = {10.5588/ijtld.22.0687},
+	abstract = {We provide an overview of the latest evidence on computer-aided detection (CAD) software for automated interpretation of chest radiographs (CXRs) for TB detection. CAD is a useful tool that can assist in rapid and consistent CXR interpretation for TB. CAD can achieve high sensitivity TB detection among people seeking care with symptoms of TB and in population-based screening, has accuracy on-par with human readers. However, implementation challenges remain. Due to diagnostic heterogeneity between settings and sub-populations, users need to select threshold scores rather than use pre-specified ones, but some sites may lack the resources and data to do so. Efficient standardisation is further complicated by frequent updates and new CAD versions, which also challenges implementation and comparison. CAD has not been validated for TB diagnosis in children and its accuracy for identifying non-TB abnormalities remains to be evaluated. A number of economic and political issues also remain to be addressed through regulation for CAD to avoid furthering health inequities. Although CAD-based CXR analysis has proven remarkably accurate for TB detection in adults, the above issues need to be addressed to ensure that the technology meets the needs of high-burden settings and vulnerable sub-populations.},
+	journal = {INT J TUBERC LUNG DIS},
+    volume = {27},
+	journaltitle = {International Journal of Tuberculosis and Lung Diseases (to appear)},
+	author = {Geric, C. AND Qin, Z. Z. AND Denkinger, C. M. AND Kik, S. V. AND Marais, B. AND Anjos, André AND David, P.-M. AND Khan, F. A. AND Trajman, A.},
+    year = {2023},
+    month = 5,
+	keywords = {computer-aided detection; chest radiology; pulmonary disease; tuberculosis; AI technology},
+}
+
+
+
 %%%%%%%%%%%%
 %%  2022  %%
 %%%%%%%%%%%%
@@ -25,6 +55,7 @@ @inproceedings{union-2022
           title = {Pulmonary Tuberculosis Screening from Radiological Signs on Chest X-Ray Images Using Deep Models},
       booktitle = {Union World Conference on Lung Health},
            year = {2022},
+    addendum = {(Issued from master thesis supervision)},
 	date = {2022-11-01},
    organization = {The Union},
        abstract = {Background: The World Health Organization has recently recommended the use of computer-aided detection (CAD) systems for screening pulmonary tuberculosis (PT) in Chest X-Ray images. Previous CAD models are based on direct image to probability detection techniques - and do not generalize well (from training to validation databases). We propose a method that overcomes these limitations by using radiological signs as intermediary proxies for PT detection.
@@ -46,6 +77,7 @@ @article{nsr-2022
 	pdf = {https://www.nature.com/articles/s41598-022-09675-y.pdf},
 	doi = {10.1038/s41598-022-09675-y},
 	abstract = {The segmentation of retinal vasculature from eye fundus images is a fundamental task in retinal image analysis. Over recent years, increasingly complex approaches based on sophisticated Convolutional Neural Network architectures have been pushing performance on well-established benchmark datasets. In this paper, we take a step back and analyze the real need of such complexity. We first compile and review the performance of 20 different techniques on some popular databases, and we demonstrate that a minimalistic version of a standard U-Net with several orders of magnitude less parameters, carefully trained and rigorously evaluated, closely approximates the performance of current best techniques. We then show that a cascaded extension (W-Net) reaches outstanding performance on several popular datasets, still using orders of magnitude less learnable weights than any previously published work. Furthermore, we provide the most comprehensive cross-dataset performance analysis to date, involving up to 10 different databases. Our analysis demonstrates that the retinal vessel segmentation is far from solved when considering test images that differ substantially from the training data, and that this task represents an ideal scenario for the exploration of domain adaptation techniques. In this context, we experiment with a simple self-labeling strategy that enables moderate enhancement of cross-dataset performance, indicating that there is still much room for improvement in this area. Finally, we test our approach on Artery/Vein and vessel segmentation from {OCTA} imaging problems, where we again achieve results well-aligned with the state-of-the-art, at a fraction of the model complexity available in recent literature. Code to reproduce the results in this paper is released.},
+    addendum = {(Issued from internship supervision)},
 	pages = {6174},
 	number = {1},
 	journal = {Nature Scientific Reports},
@@ -71,6 +103,7 @@ @inproceedings{cbic-2021
     pdf = {https://www.idiap.ch/~aanjos/papers/cbic-2021.pdf},
 	doi = {10.21528/CBIC2021-123},
 	shorttitle = {Development of a lung segmentation algorithm for analog imaged chest X-Ray},
+    addendum = {(Issued from internship supervision)},
     abstract = {Analog X-Ray radiography is still used in many underdeveloped regions around the world.  To allow these populations to benefit from advances in automatic computer-aided detection (CAD) systems, X-Ray films must be digitized. Unfortunately, this procedure may introduce imaging artefacts, which may severely impair the performance of such systems.
 
 This work investigates the impact digitized images may cause to deep neural networks trained for lung (semantic) segmentation on digital x-ray samples. While three public datasets for lung segmentation evaluation exist for digital samples, none are available for digitized data.  To this end, a U-Net-style architecture was trained on publicly available data, and used to predict lung segmentation on a newly annotated set of digitized images.
@@ -97,6 +130,7 @@ @misc{arxiv-2020
 	title = {The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models},
 	author = {Galdran, Adrian and Anjos, André and Dolz, José and Chakor, Hadi and Lombaert, Hervé and Ayed, Ismail Ben},
 	year = {2020},
+    addendum = {(Issued from internship supervision)},
     month = 9,
 	eprinttype = {arxiv},
     eprint        = {2009.01907},
@@ -129,6 +163,7 @@ @article{compbiomed-2020
 @misc{arxiv-2019,
    title         = {On the Evaluation and Real-World Usage Scenarios of Deep Vessel Segmentation for Retinography},
    author        = {Tim Laibacher and Andr\'e Anjos},
+   addendum = {(Issued from intership supervision)},
    year          = {2019},
    month         = 9,
    eprint        = {1909.03856},
@@ -190,6 +225,7 @@ @incollection{hopad-2019-2
   title = "Evaluation Methodologies for Biometric Presentation Attack Detection",
 	author = {Chingovska, Ivana and Mohammadi, Amir and Anjos, Andr{\'{e}} and Marcel, S{\'{e}}bastien},
   editor = "Marcel, S{\'{e}}bastien AND Nixon, Mark AND Fierrez, Julian AND Evans, Nicholas",
+  addendum = {(Issued from Ph.D co-supervision)},
   edition = "2nd edition (in press)",
   booktitle = "Handbook of Biometric Anti-Spoofing",
   publisher = "Springer-Verlag",
@@ -223,6 +259,7 @@ @article{tifs-2019
   title = {Heterogeneous Face Recognition Using Domain Specific Units},
   journal = {IEEE Transactions on Information Forensics and Security},
   year = {2019},
+  addendum = {(Issued from Ph.D co-supervision)},
   doi = {10.1109/TIFS.2018.2885284},
   url = "https://publications.idiap.ch/index.php/publications/show/3963",
   pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tifs-2018.pdf",
@@ -288,6 +325,7 @@ @misc{arxiv-2017-2
   archivePrefix = "arXiv",
   eprint = "1709.00962",
   primaryClass = "cs-se",
+  addendum = {(Issued from project co-supervision)},
   url = "https://arxiv.org/abs/1709.00962",
   pdf = "https://www.idiap.ch/~aanjos/papers/arxiv-2017-2.pdf",
   abstract = "This paper studies the problem of reproducible research in remote photoplethysmography (rPPG). Most of the work published in this domain is assessed on privately-owned databases, making it difficult to evaluate proposed algorithms in a standard and principled manner. As a consequence, we present a new, publicly available database containing a relatively large number of subjects recorded under two different lighting conditions. Also, three state-of-the-art rPPG algorithms from the literature were selected, implemented and released as open source free software. After a thorough, unbiased experimental evaluation in various settings, it is shown that none of the selected algorithms is precise enough to be used in a real-world scenario.",
@@ -380,6 +418,7 @@ @incollection{face-spoof-2016
   pages = "165--194",
   publisher = "Springer International Publishing",
   doi = "10.1007/978-3-319-28501-6_8",
+  addendum = {(Issued from Ph.D co-supervision)},
   abstract = "In this chapter, we give an overview of spoofing attacks and spoofing countermeasures for face recognition systems , with a focus on visual spectrum systems (VIS) in 2D and 3D, as well as near-infrared (NIR) and multispectral systems . We cover the existing types of spoofing attacks and report on their success to bypass several state-of-the-art face recognition systems. The results on two different face spoofing databases in VIS and one newly developed face spoofing database in NIR show that spoofing attacks present a significant security risk for face recognition systems in any part of the spectrum. The risk is partially reduced when using multispectral systems. We also give a systematic overview of the existing anti-spoofing techniques, with an analysis of their advantages and limitations and prospective for future work.",
 }
 
@@ -406,6 +445,7 @@ @article{tifs-2015
   keywords = "Biometric Verification, Counter-Measures, Counter-Spoofing, Liveness Detection, Replay, Spoofing Attacks",
   title = "On the use of client identity information for face anti-spoofing",
   journal = "IEEE Transactions on Information Forensics and Security, Special Issue on Biometric Anti-spoofing",
+  addendum = {(Issued from Ph.D co-supervision)},
   volume = "10",
   number = "4",
   month = 2,
@@ -431,6 +471,7 @@ @incollection{eob-2014
   publisher = "Springer US",
   isbn = "978-3-642-27733-7",
   doi = "10.1007/978-3-642-27733-7",
+  addendum = {(Issued from Ph.D co-supervision)},
   abstract = "Following the definition of the task of the anti-spoofing systems to discriminate between real accesses and spoofing attacks, anti-spoofing can be regarded as a binary classification problem. The spoofing databases and the evaluation methodologies for anti-spoofing systems most often comply to the standards for binary classification problems. However, the anti-spoofing systems are not destined to work stand-alone, and their main purpose is to protect a verification system from spoofing attacks. In the process of combining the decision of an anti-spoofing and a recognition system, effects on the recognition performance can be expected. Therefore, it is important to analyze the problem of anti-spoofing under the umbrella of biometric recognition systems. This brings certain requirements in the database design, as well as adapted concepts for evaluation of biometric recognition systems under spoofing attacks.",
 }
 
@@ -444,6 +485,7 @@ @incollection{eob-2014-2
   publisher = "Springer US",
   isbn = "978-3-642-27733-7",
   doi = "10.1007/978-3-642-27733-7_9212-2",
+  addendum = {(Issued from Ph.D co-supervision)},
   abstract = "Datasets for the evaluation of face verification system vulnerabilities to spoofing attacks and for the evaluation of face spoofing countermeasures.",
 }
 
@@ -457,6 +499,7 @@ @article{tifs-2014
   number = "12",
   doi = "10.1109/TIFS.2014.2349158",
   pdf = "https://www.idiap.ch/~aanjos/papers/tifs-2014.pdf",
+  addendum = {(Issued from Ph.D co-supervision)},
   abstract = "While more accurate and reliable than ever, the trustworthiness of biometric verification systems is compromised by the emergence of spoofing attacks. Responding to this threat, numerous research publications address isolated spoofing detection, resulting in efficient counter-measures for many biometric modes. However, an important, but often overlooked issue regards their engagement into a verification task and how to measure their impact on the verification systems themselves. A novel evaluation framework for verification systems under spoofing attacks, called Expected Performance and Spoofability (EPS) framework, is the major contribution of this paper. Its purpose is to serve for an objective comparison of different verification systems with regards to their verification performance and vulnerability to spoofing, taking into account the system’s application-dependent susceptibility to spoofing attacks and cost of the errors. The convenience of the proposed open-source framework is demonstrated for the face mode, by comparing the security guarantee of four baseline face verification systems before and after they are secured with anti-spoofing algorithms.",
 }
 
@@ -484,6 +527,7 @@ @incollection{hopad-2014-2
   publisher = "Springer-Verlag",
   year = "2014",
   doi = "10.1007/978-1-4471-6524-8_10",
+  addendum = {(Issued from Ph.D co-supervision)},
   abstract = "Following the definition of the task of the anti-spoofing systems to discriminate between real accesses and spoofing attacks, anti-spoofing can be regarded as a binary classification problem. The spoofing databases and the evaluation methodologies for anti-spoofing systems most often comply to the standards for binary classification problems. However the anti-spoofing systems are not destined to work stand-alone, and their main purpose is to protect a verification system from spoofing attacks. In the process of combining the decision of an anti-spoofing and a recognition system, effects on the recognition performance can be expected. Therefore, it is important to analyze the problem of anti-spoofing under the umbrella of biometric recognition systems. This brings certain requirements in the database design, as well as adapted concepts for evaluation of biometric recognition systems under spoofing attacks.",
 }
 

snsf-research-output.tex

@@ -97,7 +97,7 @@
 \section{Research Output for André Anjos (\thestartyear\ -- \thecurrentyear)}
 
 \cvitem{Complete list}{\url{https://anjos.ai}}
-\cvitem{H-index}{ = 27, 20000+ citations}
+\cvitem{H-index}{ = 27, 23000+ citations}
 \cvitem{Scholar}{\url{http://scholar.google.com/citations?hl=en&user=pAfLhMoAAAAJ}}
 
 % for numerical labels: \renewcommand{\bibliographyitemlabel}{\@biblabel{\arabic{enumiv}}}
@@ -114,14 +114,6 @@ \section{Research Output for André Anjos (\thestartyear\ -- \thecurrentyear)}
 
 \printbibliography[title={Open Access Archive}, type=misc]
 
-\section{Open Data}
-
-\begin{description}
-  \item[2017] \textit{COHFACE} - A dataset for remote photoplethysmography
-    using RGB data in realistic conditions;
-    URL: \url{https://www.idiap.ch/dataset/cohface}
-\end{description}
-
 \section{Open Software}
 
 \begin{description}

snsf-sinergia-cv.tex

@@ -73,7 +73,7 @@ \section{André Anjos -- Researcher, Head of Biosignal Processing
 \cvlanguage{Phone:}{+41277217763}{}
 \cvlanguage{E-mail:}{[email protected]}{}
 \cvlanguage{Website:}{\url{https://anjos.ai}}{}
-\cvlanguage{H-index:}{27}{}
+\cvlanguage{H-index:}{27 (23000+ citations)}{}
 \cvlanguage{Scholar:}{\url{https://scholar.google.ch/citations?user=pAfLhMoAAAAJ&hl=en}}{}
 \cvlanguage{ORCid}{\url{https://orcid.org/0000-0001-7248-4014}}{}
 
@@ -87,7 +87,10 @@ \section{Professional and Academic Experience}
 
 \cventry{2004--2010}{Researcher}{}{University of Wisconsin, Madison, USA}{}{Development and construction of the ATLAS Trigger and Data-Acquisition Systems, at \href{http://www.cern.ch}{CERN}, Switzerland.}
 
-\section{Research Projects}
+\section{Funding}
+
+\cventry{2022--2023}{Idiap "CAD4IED"}{Computer-Aided Diagnosis for Inflammatory
+Eye Diseases}{}{}{Budget: 160'000 CHF (Idiap: 80'000 CHF)}
 
 \cventry{2022--2023}{The Ark Foundation "SECure"}{Safe \& Explainable Clinical AI}{}{}{Budget: 330'838 CHF (Idiap: 129'833 CHF)}
 
@@ -112,16 +115,18 @@ \section{Research Projects}
 \cventry{2012--2016}{EU/FP7 "BEAT"}{Biometric Evaluation Platform}{}{}{Budget:
 4'755'871 CHF (Idiap: 1'217'741 CHF)}
 
-\section{Supervision and Contributions}
+\section{Student Supervision}
 
+\cventry{2022--}{Doctoral Student}{Maxime Délitroz}{Discovery of Early Biomarkers for Glaucoma using AI}{}{}
 \cventry{2022--2023}{Master Student}{Samuel Michel}{Automatic Sleep-Phase Detection for Polysomnography}{}{}
-\cventry{2021--2022}{Master Student}{Antonio Morais}{Bayesian Confidence-Interval Estimation with Non-i.i.d. Samples}{}{}
-\cventry{2021--2022}{Master Student}{Driss Khalil}{Multi-Task Learning for Semantic Segmentation}{}{}
+%\cventry{2021--2022}{Master Student}{Antonio Morais}{Bayesian Confidence-Interval Estimation with Non-i.i.d. Samples}{}{}
+%\cventry{2021--2022}{Master Student}{Driss Khalil}{Multi-Task Learning for Semantic Segmentation}{}{}
 \cventry{2020--2021}{Master Student}{Geoffrey Raposo}{Active Tuberculosis exclusion from frontal chest X-ray images}{}{}
 \cventry{2019--2020}{Master Student}{Colombine Verzat}{Adverse event Detection
 for Latent Tuberculosis Infection Treatment}{}{}
 \cventry{2019}{Intern}{Tim Laibacher}{Semantic Segmentation of Medical Imaging}{}{}
-\cventry{2011--2015}{Doctoral Student}{\href{http://www.idiap.ch/~ichingo/}{Ivana Chingovska}}{Thesis work associated with the FP7 TABULA RASA project}{}{}
+\cventry{2016--2019}{Doctoral Student}{Tiago de Freitas Pereira}{Heterogeneous Face Recognition}{}{}
+\cventry{2011--2015}{Doctoral Student}{Ivana Chingovska}{Presentation-Attack Detection in Face Biometrics}{}{}
 
 \section{Memberships and Committes}
 
@@ -136,7 +141,7 @@ \section{Organization of Conferences}
 \cventry{2016}{IAPR International Conference on Biometrics}{Program Committee}{}{}{}
 \cventry{2015}{IEEE International Conference on Biometrics: Theory, Applications, and Systems}{Participation on Doctoral Consortium}{}{}{}
 
-\section{Outreach (Teaching)}
+\section{Teaching}
 
 \cventry{2022}{\href{https://www.ifi.uzh.ch/en/studies/phd/summer-schools.html}{UZH/IFI Summer School}}{}{Invited Course on Reproducibility}{2022}{}{}