Yashin Dicente Cid

Roche · Roche Tissue Diagnostics

This paper presents an overview of the ImageCLEF 2022 lab that was organized as part of the Conference and Labs of the Evaluation Forum – CLEF Labs 2022. ImageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing infor...

ImageCLEF is part of the Conference and Labs of the Evaluation Forum (CLEF) since 2003. CLEF 2022 will take place in Bologna, Italy. ImageCLEF is an ongoing evaluation initiative which promotes the evaluation of technologies for annotation, indexing, and retrieval of visual data with the aim of providing information access to large collections of i...

This paper presents an overview of the ImageCLEF 2021 lab that was organized as part of the Conference and Labs of the Evaluation Forum – CLEF Labs 2021. ImageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing infor...

This paper presents an overview of the ImageCLEF 2021 lab that was organized as part of the Conference and Labs of the Evaluation Forum-CLEF Labs 2021. ImageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing informa...

ImageCLEF is a part of the Conference and Labs of the Evaluation Forum (CLEF) initiative and includes a variety of tasks dedicated to multimodal image information retrieval, including image classification and annotation. The tuberculosis (TB) task is one of the ImageCLEF tasks which started in 2017 and changed from year to year. The 2021 edition wa...

Selective attention is the ability to promote the processing of objects important for the accomplishment of our behavioral goals (target objects) over the objects not important to those goals (distractor objects). Previous investigations have shown that the mechanisms of selective attention contribute to enhancing perception in both simple daily ta...

PJM & DS - joint senior authorship Selective attention is the ability to promote the processing of objects important for the accomplishment of our behavioral goals (target objects) over the objects not important to those goals (distractor objects). Previous investigations have shown that the mechanisms of selective attention contribute to enhanci...

Since its dawn as a discipline, Artificial Intelligence (AI) has focused on mimicking the human mental processes. As AI applications matured, the interest for employing them into real-world complex systems (i.e., coupling AI with Cyber-Physical Systems—CPS) kept increasing. In the last decades, the multi-agent systems (MAS) paradigm has been among...

This paper presents the ideas for the 2021 ImageCLEF lab that will be organized as part of the Conference and Labs of the Evaluation Forum—CLEF Labs 2021 in Bucharest, Romania. ImageCLEF is an ongoing evaluation initiative (active since 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the...

This paper presents the ideas for the 2021 ImageCLEF lab that will be organized as part of the Conference and Labs of the Evaluation Forum-CLEF Labs 2021 in Bucharest, Romania. ImageCLEF is an ongoing evaluation initiative (active since 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the...

ImageCLEF is a part of the Conference and Labs of the Evaluation Forum (CLEF) initiative and presents a set of image information retrieval tasks. ImageCLEF was historically focused on the variety of multimodal image classification, retrieval and annotation tasks. The tuberculosis task started in ImageCLEF in 2017 and changed from year to year. This...

This paper presents an overview of the ImageCLEF 2020 lab that was organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2020. ImageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing infor...

This paper presents an overview of the ImageCLEF 2020 lab that was organized as part of the Conference and Labs of the Evaluation Forum-CLEF Labs 2020. ImageCLEF is an ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing informa...

Chronic thromboembolic pulmonary hypertension (CTEPH) is a possible complication of pulmonary embolism (PE), with poor prognosis if left untreated. Surgical curative treatment is available, particularly in the early stages of the disease. However, most cases are not diagnosed until specific symptoms become evident. A small number of computed tomogr...

Using medical images recorded in clinical practice has the potential to be a game-changer in the application of machine learning for medical decision support. Thousands of medical images are produced in daily clinical activity. The diagnosis of medical doctors on these images represents a source of knowledge to train machine learning algorithms for...

This paper presents an overview of the 2020 ImageCLEF lab that will be organized as part of the Conference and Labs of the Evaluation Forum—CLEF Labs 2020 in Thessaloniki, Greece. ImageCLEF is an ongoing evaluation initiative (run since 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the...

This paper presents an overview of the 2020 ImageCLEF lab that will be organized as part of the Conference and Labs of the Evaluation Forum-CLEF Labs 2020 in Thessaloniki, Greece. ImageCLEF is an ongoing evaluation initiative (run since 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the...

ImageCLEF is the image retrieval task of the Conference and Labs of the Evaluation Forum (CLEF). ImageCLEF has historically focused on the multimodal and language-independent retrieval of images. Many tasks are related to image classification and the annotation of image data as well as the retrieval of images. Since 2017, when the tuberculosis task...

This paper presents an overview of the ImageCLEF 2019 lab, organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2019. ImageCLEF is an ongoing evaluation initiative (started in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information acc...

Although remarkable improvements have been made, the natural control of hand prostheses in everyday life is still challenging. Changes in limb position can considerably affect the robustness of pattern recognition-based myoelectric control systems, even if various strategies were proposed to mitigate this effect. In this paper, we investigate the p...

Pulmonary tuberculosis (TB) is still an important cause of death worldwide, even after being almost eradicated 40 years ago. Early identification of TB in computed tomography (CT) scans can influence therapeutical decisions, thus improving patient outcome. In this paper, a graph model of the lungs is proposed for the classification of TB types usin...

This paper presents an overview of the foreseen ImageCLEF 2019 lab that will be organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2019. ImageCLEF is an ongoing evaluation initiative (started in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of prov...

This paper presents an overview of the foreseen ImageCLEF 2019 lab that will be organized as part of the Conference and Labs of the Evaluation Forum-CLEF Labs 2019. ImageCLEF is an ongoing evaluation initiative (started in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of provid...

Yashin Dicente Cid 1[0000−0001−7742−5363] , Oscar Jiménez-del-Toro 1,2,3[0000−0002−0628−3764] , Pierre-Alexandre Poletti 3[0000−0001−9214−5546] , and Henning Müller 1,2[0000−0001−6800−9878] Abstract. Pulmonary tuberculosis (TB) is still an important cause of death worldwide, even after being almost eradicated 40 years ago. Early identification of T...

Purpose The aims of this multicentre retrospective study of locally advanced head and neck cancer (LAHNC) treated with definitive radiotherapy were to (1) identify positron emission tomography (PET)-¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) parameters correlated with overall survival (OS) in a training cohort, (2) compute a prognostic model, and (3) externa...

Lung image analysis is an essential part in the assessment of pulmonary diseases. Through visual inspection of CT scans, radiologists detect abnormal patterns in the lung parenchyma, aiming to establish a timely diagnosis and thus improving patient outcome. However, in a generalized disorder of the lungs, such as pulmonary hypertension, the changes...

Lung image analysis is an essential part in the assessment of pulmonary diseases. Through visual inspection of CT scans, radiologists detect abnormal patterns in the lung parenchyma, aiming to establish a timely diagnosis and thus improving patient outcome. However, in a generalized disorder of the lungs, such as pulmonary hypertension, the changes...

Tuberculosis (TB) remains a leading cause of death worldwide. Two main challenges when assessing computed tomography scans of TB patients are detecting multi-drug resistance and differentiating TB types. In this article we model the lungs as a graph entity where nodes represent anatomical lung regions and edges encode interactions between them. Thi...

ImageCLEF is the image retrieval task of the Conference and Labs of the Evaluation Forum (CLEF). ImageCLEF has historically focused on the multimodal and language-independent retrieval of images. Many tasks are related to image classification and the annotation of image data as well as the retrieval of images. The tuberculosis task was held for the...

In 2018, ImageCLEF proposed a task using CT (Computed Tomography) scans of patients with tuberculosis (TB). The task was divided into three subtasks: multi-drug resistance detection, TB type classification , and severity scoring. In this work we present a graph model of the lungs capable of characterizing TB patients with different lung problems. T...

Medical imaging plays an important role in patient diagnosis and treatment planning. A standard procedure to assess a respiratory disease is a CT scan of the chest, where radiologists can detect subtle alterations in the lung tissue. This thesis aims at describing the lung tissue in CT scans, both from a local and a global perspective. It explores...

Objectif de l’étude Les objectifs de ce travail étaient d’identifier, pour des cancers non oropharyngé localement évolués pris en charge par chimioradiothérapie, des paramètres de tomographie par émission de positons (TEP) quantitatifs prédictif de la survie sans progression et dans un second temps d’établir un score pronostique. Matériel et métho...

This paper presents an overview of the ImageCLEF 2017 evaluation campaign, an event that was organized as part of the CLEF (Conference and Labs of the Evaluation Forum) labs 2017. ImageCLEF is an ongoing initiative (started in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval for providing information access...

Many image acquisition techniques used in biomedical imaging, material analysis, and structural geology are capable of acquiring 3–D solid images. Computational analysis of these images is complex but necessary since it is difficult for humans to visualize and quantify their detailed 3–D content. One of the most common methods to analyze 3–D data i...

This article presents a novel graph–model approach encoding the relations between the perfusion in several regions of the lung extracted from a geometry–based atlas. Unlike previous approaches that individually analyze regions of the lungs, our method evaluates the entire pulmonary circulatory network for the classification of patients with pulmona...

This paper proposes a novel imaging biomarker of lung cancer relapse from 3-D texture analysis of CT images. Three-dimensional morphological nodular tissue properties are described in terms of 3-D Riesz-wavelets. The responses of the latter are aggregated within nodular regions by means of feature covariances, which leverage rich intra- and inter-...

Variations in the shape and appearance of anatomical structures in medical images are often relevant radiological signs of disease. Automatic tools can help automate parts of this manual process. A cloud-based evaluation framework is presented in this paper including results of benchmarking current state-of-the-art medical imaging algorithms for an...

Medical image analysis techniques require an initial localization and segmentation of the corresponding anatomical structures. As part of the VISCERAL Anatomy segmentation benchmarks, a hierarchical multi-atlas multi-structure segmentation approach guided by anatomical correlations is proposed (AnatSeg-Gspac). The method defines a global alignment...

The segmentation of lung volumes constitutes the first step for most computer–aided systems for lung diseases. CT (Computed Tomography) is the most common imaging technique used by these systems, so fast and accurate methods are needed to for allow early and reliable analysis. In this paper, an efficient and fully automatic method for the segmentat...

In this paper we provide an integrated approach for matching patterns in scenes combining 3D and visual information. For local definition of points we propose a descriptor based on the notion of covariance of features for fusion of shape and color information of 3D surfaces, so-called multi-scale covariance descriptor (MCOV). The intrinsic properti...

Clinicians searching through the large data sets of multimodal medical information generated in hospitals currently do not fully exploit previous medical cases to retrieve relevant information for a differential diagnosis. The VISCERAL Retrieval benchmark organized a medical case–based retrieval evaluation using a data set composed of patient scans...