PSFHS challenge report: Pubic symphysis and fetal head segmentation from intrapartum ultrasound images.

Autor: Bai J; Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Jinan University, Guangzhou, China; Auckland Bioengineering Institute, The University of Auckland, Private Bag 92019, Auckland 1142, New Zealand. Electronic address: jbai996@aucklanduni.ac.nz., Zhou Z; Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Jinan University, Guangzhou, China., Ou Z; Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Jinan University, Guangzhou, China., Koehler G; Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany., Stock R; Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany., Maier-Hein K; Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany., Elbatel M; Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hongkong, China., Martí R; Computer Vision and Robotics Group, University of Girona, Girona, Spain., Li X; Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hongkong, China., Qiu Y; Canon Medical Systems (China) Co., LTD, Beijing, China., Gou P; Canon Medical Systems (China) Co., LTD, Beijing, China., Chen G; College of Artificial Intelligence, Nankai University, Tianjin, China., Zhao L; College of Computer Science and Electronic Engineering, Hunan University, Changsha, China., Zhang J; College of Artificial Intelligence, Nankai University, Tianjin, China., Dai Y; College of Artificial Intelligence, Nankai University, Tianjin, China., Wang F; School of Medicine, University College Dublin, Dublin, Ireland., Silvestre G; School of Medicine, University College Dublin, Dublin, Ireland., Curran K; School of Computer Science, University College Dublin, Dublin, Ireland., Sun H; School of Statistics & Mathematics, Zhejiang Gongshang University, Hangzhou, China., Xu J; School of Statistics & Mathematics, Zhejiang Gongshang University, Hangzhou, China., Cai P; School of Computer Science & Engineering, Chongqing University of Technology, Chongqing, China., Jiang L; School of Computer Science & Engineering, Chongqing University of Technology, Chongqing, China., Lan L; School of Computer Science & Engineering, Chongqing University of Technology, Chongqing, China., Ni D; National-Regional Key Technology Engineering Laboratory for Medical Ultrasound & Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging & School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China., Zhong M; NanFang Hospital of Southern Medical University, Guangzhou, China., Chen G; Zhujiang Hospital of Southern Medical University, Guangzhou, China., Campello VM; Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain., Lu Y; Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Jinan University, Guangzhou, China., Lekadir K; Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.

Publikováno v: Medical image analysis [Med Image Anal] 2025 Jan; Vol. 99, pp. 103353. Date of Electronic Publication: 2024 Sep 21.

Image-Based Biological Heart Age Estimation Reveals Differential Aging Patterns Across Cardiac Chambers.

Autor: Salih AM; William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK., Pujadas ER; Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Artificial Intelligence in Medicine Lab (BCN-AIM), Barcelona, Spain., Campello VM; Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Artificial Intelligence in Medicine Lab (BCN-AIM), Barcelona, Spain., McCracken C; Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK., Harvey NC; MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK.; NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK., Neubauer S; Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK., Lekadir K; Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Artificial Intelligence in Medicine Lab (BCN-AIM), Barcelona, Spain., Nichols TE; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, UK., Petersen SE; William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK.; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK.; Health Data Research UK, London, UK.; Alan Turing Institute, London, UK., Raisi-Estabragh Z; William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK.; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, UK.

Publikováno v: Journal of magnetic resonance imaging : JMRI [J Magn Reson Imaging] 2023 Dec; Vol. 58 (6), pp. 1797-1812. Date of Electronic Publication: 2023 Mar 16.

Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.

Autor: Martin-Isla C, Campello VM, Izquierdo C, Kushibar K, Sendra-Balcells C, Gkontra P, Sojoudi A, Fulton MJ, Arega TW, Punithakumar K, Li L, Sun X, Al Khalil Y, Liu D, Jabbar S, Queiros S, Galati F, Mazher M, Gao Z, Beetz M, Tautz L, Galazis C, Varela M, Hullebrand M, Grau V, Zhuang X, Puig D, Zuluaga MA, Mohy-Ud-Din H, Metaxas D, Breeuwer M, van der Geest RJ, Noga M, Bricq S, Rentschler ME, Guala A, Petersen SE, Escalera S, Palomares JFR, Lekadir K

Publikováno v: IEEE journal of biomedical and health informatics [IEEE J Biomed Health Inform] 2023 Jul; Vol. 27 (7), pp. 3302-3313. Date of Electronic Publication: 2023 Jun 30.

Author Correction: Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countries.

Autor: Sendra-Balcells C; Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain. carla.sendra@ub.edu., Campello VM; Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain. victor.campello@ub.edu., Torrents-Barrena J; HP Inc., Barcelona, Spain., Ahmed YA; Obstetrics and Gynecology Department, School of Medicine, Suez University, Suez, Egypt., Elattar M; Medical Imaging and Image Processing, Center of Informatics Science, Nile University, Sheikh Zayed City , Egypt.; Research and Development Division, Intixel, Cairo , Egypt., Ohene-Botwe B; Department of Radiography, School of Biomedical and Allied Health Sciences, College of Health Sciences, University of Ghana, Accra , Ghana.; Division of Midwifery and Radiography, School of Health and Psychological Sciences, University of London, London, UK., Nyangulu P; Kamuzu University of Health Sciences, Blantyre, Malawi., Stones W; Kamuzu University of Health Sciences, Blantyre, Malawi., Ammar M; Department of Electrical Engineering Systems, Laboratory of Engineering System and Telecommunication, University of M'Hamed Bougara Boumerdes, Algiers, Algeria., Benamer LN; Obstetrics and Gynecology Department, School of Medicine, Algiers University, Algiers, Algeria., Kisembo HN; Department of Radiology, Mulago National Referral and Teaching Hospital, Kampala, Uganda., Sereke SG; Department of Radiology and Radiotherapy, School of Medicine, Makerere University College of Health Sciences, Kampala, Uganda., Wanyonyi SZ; Department of Obstetrics and Gynaecology, Aga Khan University Hospital, 3rd Parklands Avenue, Nairobi, Kenya., Temmerman M; Centre of Excellence in Women and Child Health, Aga Khan University, Nairobi, Kenya., Gratacós E; BCNatal Fetal Medicine Research Center, Hospital Clínic and Hospital Sant Joan de Déu, Universitat de Barcelona, Barcelona, Spain.; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.; Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain., Bonet E; BCNatal Fetal Medicine Research Center, Hospital Clínic and Hospital Sant Joan de Déu, Universitat de Barcelona, Barcelona, Spain.; Barcelona Tech, Universitat Politècnica de Catalunya, Barcelona, Spain., Eixarch E; BCNatal Fetal Medicine Research Center, Hospital Clínic and Hospital Sant Joan de Déu, Universitat de Barcelona, Barcelona, Spain.; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.; Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain., Mikolaj K; Copenhagen Academy for Medical Education and Simulation and Department of Obstetrics, Rigshospitalet, Copenhagen, Denmark., Tolsgaard MG; Copenhagen Academy for Medical Education and Simulation and Department of Obstetrics, Rigshospitalet, Copenhagen, Denmark., Lekadir K; Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain.

Publikováno v: Scientific reports [Sci Rep] 2023 Feb 28; Vol. 13 (1), pp. 3410. Date of Electronic Publication: 2023 Feb 28.

Atrial fibrillation prediction by combining ECG markers and CMR radiomics.

Autor: Pujadas ER; Artificial Intelligence in Medicine Lab (BCN-AIM), Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain. esmeralda.ruiz@ub.edu., Raisi-Estabragh Z; William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, EC1A 7BE, UK., Szabo L; William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, EC1A 7BE, UK., Morcillo CI; Artificial Intelligence in Medicine Lab (BCN-AIM), Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain., Campello VM; Artificial Intelligence in Medicine Lab (BCN-AIM), Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain., Martin-Isla C; Artificial Intelligence in Medicine Lab (BCN-AIM), Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain., Vago H; Semmelweis University Heart and Vascular Center, Budapest, Hungary., Merkely B; Semmelweis University Heart and Vascular Center, Budapest, Hungary., Harvey NC; MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK.; NIHR Southampton Biomedical Research Centre, University of Southampton, University Hospital Southampton NHS Foundation Trust, Southampton, UK., Petersen SE; William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.; Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, EC1A 7BE, UK.; Health Data Research UK, London, UK.; Alan Turing Institute, London, UK., Lekadir K; Artificial Intelligence in Medicine Lab (BCN-AIM), Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain.

Publikováno v: Scientific reports [Sci Rep] 2022 Nov 07; Vol. 12 (1), pp. 18876. Date of Electronic Publication: 2022 Nov 07.