Daniel Capellan-Martin

@upm.es

Machine Learning Researcher & Phd Student
Biomedical Image Technologies, Universidad Politécnica de Madrid

Daniel Capellan-Martin


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https://researchid.co/dani-capellan

EDUCATION

B.Sc. in Biomedical Engineering
M.Sc. in Biomedical Engineering
M.Sc. in Technological Innovation in Health
Ph.D. in Biomedical Engineering & Artificial Intelligence (currently)

RESEARCH INTERESTS

Artificial Intelligence
Machine Learning
Deep Learning
Medical Imaging
Pediatric imaging
Chest X-Ray imaging
Cardiac imaging
Image processing
Signal Processing
188

Scholar Citations

8

Scholar h-index

8

Scholar i10-index

RECENT SCHOLAR PUBLICATIONS

  • Improving Pre-trained Segmentation Models using Post-Processing
    A Parida, D Capellán-Martín, Z Jiang, N Kulkarni, K Iyer, A Tapp, ...
    arXiv preprint arXiv:2512.14937 , 2025
    2025
    Citations: 1
  • Diagnostic Performance of Chest Radiography for Pediatric Tuberculosis Across High-and Low-Burden Settings
    A Hernanz Lobo, JJ Gómez Valverde, Á Lancharro, R Sánchez-Jacob, ...
    Frontiers in Pediatrics 13, 1704149 , 2025
    2025
    Citations: 1
  • Multi-view deep learning framework for the detection of chest X-rays compatible with pediatric pulmonary tuberculosis
    D Capellán-Martín, JJ Gómez-Valverde, R Sánchez-Jacob, ...
    Nature communications 16 (1), 9170 , 2025
    2025
    Citations: 6
  • Improving Pre-trained Adult Glioma Segmentation Models Using only Post-processing Techniques
    A Parida, D Capellán-Martín, Z Jiang, N Kulkarni, K Iyer, A Tapp, ...
    International Conference on Medical Image Computing and Computer-Assisted … , 2025
    2025
  • Adaptable Segmentation Pipeline for Diverse Brain Tumors with Radiomic-Guided Subtyping and Lesion-Wise Model Ensemble
    D Capellán-Martín, A Parida, Z Jiang, N Kulkarni, K Iyer, A Tapp, ...
    International Conference on Medical Image Computing and Computer-Assisted … , 2025
    2025
    Citations: 1
  • Post-processing Methods for Improving Accuracy in MRI Inpainting
    N Kulkarni, K Iyer, A Tapp, A Parida, D Capellán-Martín, Z Jiang, ...
    International Conference on Medical Image Computing and Computer-Assisted … , 2025
    2025
  • Controllable Latent Diffusion-Based 3D Brain Tumor Segmentation: With Synthetic Label Generation and Detailed Variance Map
    X Liu, P Guo, D Capellán-Martin, Z Jiang, HR Roth, A Tapp, ...
    2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), 1-5 , 2025
    2025
    Citations: 1
  • Guía de instalación de herramientas para compilación multiplataforma en C. Sistemas Digitales II, Sistemas Electrónicos
    J Pagán Ortiz, PJ Malagón Marzo, R Cárdenas Rodríguez, ...
    Josué Pagán Ortiz , 2025
    2025
  • Adult glioma segmentation in sub-saharan africa using transfer learning on stratified finetuning data
    A Parida, D Capellán-Martín, Z Jiang, A Tapp, X Liu, SM Anwar, ...
    arXiv preprint arXiv:2412.04111 , 2024
    2024
    Citations: 15
  • Magnetic resonance imaging feature-based subtyping and model ensemble for enhanced brain tumor segmentation
    Z Jiang, D Capellán-Martín, A Parida, A Tapp, X Liu, ...
    arXiv preprint arXiv:2412.04094 , 2024
    2024
    Citations: 11
  • Artificial intelligence-driven mobile interpretation of a semi-quantitative cryptococcal antigen lateral flow assay
    D Bermejo-Peláez, A Alastruey-Izquierdo, N Medina, D Capellán-Martín, ...
    IMA fungus 15 (1), 27 , 2024
    2024
    Citations: 21
  • Chest X-Ray–Based Telemedicine Platform for Pediatric Tuberculosis Diagnosis in Low-Resource Settings: Development and Validation Study
    JJ Gómez-Valverde, R Sánchez-Jacob, JL Ribó, HS Schaaf, ...
    JMIR pediatrics and parenting 7, e51743 , 2024
    2024
    Citations: 8
  • IMG-28. AUTOMATIC BRAIN TUMOR VOLUMETRIC ANALYSIS IN MAGNETIC RESONANCE IMAGING GENERALIZABLE TO PEDIATRIC NEURO-ONCOLOGY
    Z Jiang, D Capellan-Martin, A Parida, X Liu, V Lam, H Nisar, A Tapp, ...
    Neuro-Oncology 26 (Suppl 4), 0 , 2024
    2024
    Citations: 1
  • Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge
    D LaBella, V Abramova, M Astaraki, A Ferreira, Z Jiang, MC Cleveland, ...
    arXiv preprint arXiv:2405.18383 , 2024
    2024
    Citations: 1
  • Enhancing generalizability in brain tumor segmentation: Model ensemble with adaptive post-processing
    Z Jiang, D Capellán-Martín, A Parida, X Liu, MJ Ledesma-Carbayo, ...
    2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1-4 , 2024
    2024
    Citations: 10
  • Zero-shot pediatric tuberculosis detection in chest x-rays using self-supervised learning
    D Capellán-Martín, A Parida, JJ Gómez-Valverde, R Sanchez-Jacob, ...
    2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1-5 , 2024
    2024
    Citations: 8
  • Brain tumor segmentation (brats) challenge 2024: Meningioma radiotherapy planning automated segmentation
    D LaBella, V Abramova, M Astaraki, A Ferreira, Z Jiang, MC Cleveland, ...
    arXiv e-prints, arXiv: 2405.18383 , 2024
    2024
    Citations: 28
  • DiCoM--Diverse Concept Modeling towards Enhancing Generalizability in Chest X-Ray Studies
    A Parida, D Capellan-Martin, S Atito, M Awais, MJ Ledesma-Carbayo, ...
    arXiv preprint arXiv:2402.15534 , 2024
    2024
    Citations: 4
  • Model ensemble for brain tumor segmentation in magnetic resonance imaging
    D Capellán-Martín, Z Jiang, A Parida, X Liu, V Lam, H Nisar, A Tapp, ...
    International Challenge on Cross-Modality Domain Adaptation for Medical … , 2023
    2023
    Citations: 29
  • A lightweight, rapid and efficient deep convolutional network for chest x-ray tuberculosis detection
    D Capellán-Martín, JJ Gómez-Valverde, D Bermejo-Peláez, ...
    2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 1-5 , 2023
    2023
    Citations: 25

MOST CITED SCHOLAR PUBLICATIONS

  • Model ensemble for brain tumor segmentation in magnetic resonance imaging
    D Capellán-Martín, Z Jiang, A Parida, X Liu, V Lam, H Nisar, A Tapp, ...
    International Challenge on Cross-Modality Domain Adaptation for Medical … , 2023
    2023
    Citations: 29
  • Brain tumor segmentation (brats) challenge 2024: Meningioma radiotherapy planning automated segmentation
    D LaBella, V Abramova, M Astaraki, A Ferreira, Z Jiang, MC Cleveland, ...
    arXiv e-prints, arXiv: 2405.18383 , 2024
    2024
    Citations: 28
  • A lightweight, rapid and efficient deep convolutional network for chest x-ray tuberculosis detection
    D Capellán-Martín, JJ Gómez-Valverde, D Bermejo-Peláez, ...
    2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 1-5 , 2023
    2023
    Citations: 25
  • Artificial intelligence-driven mobile interpretation of a semi-quantitative cryptococcal antigen lateral flow assay
    D Bermejo-Peláez, A Alastruey-Izquierdo, N Medina, D Capellán-Martín, ...
    IMA fungus 15 (1), 27 , 2024
    2024
    Citations: 21
  • Adult glioma segmentation in sub-saharan africa using transfer learning on stratified finetuning data
    A Parida, D Capellán-Martín, Z Jiang, A Tapp, X Liu, SM Anwar, ...
    arXiv preprint arXiv:2412.04111 , 2024
    2024
    Citations: 15
  • Combining collective and artificial intelligence for global health diseases diagnosis using crowdsourced annotated medical images
    L Lin, D Bermejo-Peláez, D Capellán-Martín, D Cuadrado, C Rodríguez, ...
    2021 43rd Annual International Conference of the IEEE Engineering in … , 2021
    2021
    Citations: 14
  • Magnetic resonance imaging feature-based subtyping and model ensemble for enhanced brain tumor segmentation
    Z Jiang, D Capellán-Martín, A Parida, A Tapp, X Liu, ...
    arXiv preprint arXiv:2412.04094 , 2024
    2024
    Citations: 11
  • Enhancing generalizability in brain tumor segmentation: Model ensemble with adaptive post-processing
    Z Jiang, D Capellán-Martín, A Parida, X Liu, MJ Ledesma-Carbayo, ...
    2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1-4 , 2024
    2024
    Citations: 10
  • Chest X-Ray–Based Telemedicine Platform for Pediatric Tuberculosis Diagnosis in Low-Resource Settings: Development and Validation Study
    JJ Gómez-Valverde, R Sánchez-Jacob, JL Ribó, HS Schaaf, ...
    JMIR pediatrics and parenting 7, e51743 , 2024
    2024
    Citations: 8
  • Zero-shot pediatric tuberculosis detection in chest x-rays using self-supervised learning
    D Capellán-Martín, A Parida, JJ Gómez-Valverde, R Sanchez-Jacob, ...
    2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1-5 , 2024
    2024
    Citations: 8
  • Multi-view deep learning framework for the detection of chest X-rays compatible with pediatric pulmonary tuberculosis
    D Capellán-Martín, JJ Gómez-Valverde, R Sánchez-Jacob, ...
    Nature communications 16 (1), 9170 , 2025
    2025
    Citations: 6
  • DiCoM--Diverse Concept Modeling towards Enhancing Generalizability in Chest X-Ray Studies
    A Parida, D Capellan-Martin, S Atito, M Awais, MJ Ledesma-Carbayo, ...
    arXiv preprint arXiv:2402.15534 , 2024
    2024
    Citations: 4
  • Deep learning-based lung segmentation and automatic regional template in chest X-ray images for pediatric tuberculosis
    D Capellán-Martín, JJ Gómez-Valverde, R Sanchez-Jacob, ...
    arXiv preprint arXiv:2301.13786 , 2023
    2023
    Citations: 3
  • Improving Pre-trained Segmentation Models using Post-Processing
    A Parida, D Capellán-Martín, Z Jiang, N Kulkarni, K Iyer, A Tapp, ...
    arXiv preprint arXiv:2512.14937 , 2025
    2025
    Citations: 1
  • Diagnostic Performance of Chest Radiography for Pediatric Tuberculosis Across High-and Low-Burden Settings
    A Hernanz Lobo, JJ Gómez Valverde, Á Lancharro, R Sánchez-Jacob, ...
    Frontiers in Pediatrics 13, 1704149 , 2025
    2025
    Citations: 1
  • Adaptable Segmentation Pipeline for Diverse Brain Tumors with Radiomic-Guided Subtyping and Lesion-Wise Model Ensemble
    D Capellán-Martín, A Parida, Z Jiang, N Kulkarni, K Iyer, A Tapp, ...
    International Conference on Medical Image Computing and Computer-Assisted … , 2025
    2025
    Citations: 1
  • Controllable Latent Diffusion-Based 3D Brain Tumor Segmentation: With Synthetic Label Generation and Detailed Variance Map
    X Liu, P Guo, D Capellán-Martin, Z Jiang, HR Roth, A Tapp, ...
    2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), 1-5 , 2025
    2025
    Citations: 1
  • IMG-28. AUTOMATIC BRAIN TUMOR VOLUMETRIC ANALYSIS IN MAGNETIC RESONANCE IMAGING GENERALIZABLE TO PEDIATRIC NEURO-ONCOLOGY
    Z Jiang, D Capellan-Martin, A Parida, X Liu, V Lam, H Nisar, A Tapp, ...
    Neuro-Oncology 26 (Suppl 4), 0 , 2024
    2024
    Citations: 1
  • Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge
    D LaBella, V Abramova, M Astaraki, A Ferreira, Z Jiang, MC Cleveland, ...
    arXiv preprint arXiv:2405.18383 , 2024
    2024
    Citations: 1
  • Improving Pre-trained Adult Glioma Segmentation Models Using only Post-processing Techniques
    A Parida, D Capellán-Martín, Z Jiang, N Kulkarni, K Iyer, A Tapp, ...
    International Conference on Medical Image Computing and Computer-Assisted … , 2025
    2025