AI-Dentify: deep learning for proximal caries detection on bitewing x-ray - HUNT4 Oral Health Study

Autor: Javier Pérez de Frutos, Ragnhild Holden Helland, Shreya Desai, Line Cathrine Nymoen, Thomas Langø, Theodor Remman, Abhijit Sen

Publikováno v: BMC Oral Health, Vol 24, Iss 1, Pp 1-10 (2024)

Abstract Background Dental caries diagnosis requires the manual inspection of diagnostic bitewing images of the patient, followed by a visual inspection and probing of the identified dental pieces with potential lesions. Yet the use of artificial int

Externí odkaz: https://doaj.org/article/095a72cdf2054bb29c9d12aaadda2ea6

Learning deep abdominal CT registration through adaptive loss weighting and synthetic data generation

Autor: Javier Pérez de Frutos, André Pedersen, Egidijus Pelanis, David Bouget, Shanmugapriya Survarachakan, Thomas Langø, Ole-Jakob Elle, Frank Lindseth

Purpose: This study aims to explore training strategies to improve convolutional neural network-based image-to-image deformable registration for abdominal imaging. Methods: Different training strategies, loss functions, and transfer learning schemes

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a212b32d17c2f1492139ee1fcf99416
http://arxiv.org/abs/2211.15717

FastPathology: An open-source platform for deep learning-based research and decision support in digital pathology

Autor: Anna M. Bofin, Ingerid Reinertsen, Erik Smistad, André Pedersen, Javier Pérez de Frutos, Marit Valla

Publikováno v: IEEE Access
IEEE Access, Vol 9, Pp 58216-58229 (2021)
58216-58229

Deep convolutional neural networks (CNNs) are the current state-of-the-art for digital analysis of histopathological images. The large size of whole-slide microscopy images (WSIs) requires advanced memory handling to read, display and process these i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d4d3663f3b1ca2becf97e16d7c9cb003
http://arxiv.org/abs/2011.06033

Current trends in reconfigurable modular robots design

Autor: E. Gambao, Alberto Brunete, Javier Pérez de Frutos, Miguel Hernando, Sergio Segovia, Avinash Ranganath

Publikováno v: International Journal of Advanced Robotic Systems, Vol 14 (2017)
International Journal of Advanced Robotic Systems, ISSN 1729-8814, 2017-05, Vol. 14, No. 3
Archivo Digital UPM
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This article presents a review on trends in modular reconfigurable robots, comparing the evolution of the features of the most significant robots over the years and focusing on the latest designs. These features are reconfiguration, docking, degrees

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a120cb42f390adf3eda70915003a7eb3
https://doaj.org/article/4a691d12b5d74fe09e2d35bcc38115f2

Influence of sampling accuracy on augmented reality for laparoscopic image-guided surgery

Autor: Javier Pérez de Frutos, Bjørn Edwin, Davit L. Aghayan, Andrea Teatini, Benjamin Eigl, Marco Lai, Ole Jakob Elle, Egidijus Pelanis, Rafael Palomar, Rahul Prasanna Kumar

Publikováno v: Teatini, Andrea; Pérez de Frutos, Javier; Eigl, Benjamin; Pelanis, Egidijus; Aghayan, Davit L.; Lai, Marco; Kumar, Rahul Prasanna; Palomar, Rafael; Edwin, Bjørn; Elle, Ole Jakob (2021). Influence of sampling accuracy on augmented reality for laparoscopic image-guided surgery. Minimally invasive therapy & allied technologies, 30(4), pp. 229-238. Taylor & Francis Group 10.1080/13645706.2020.1727524
Minimally Invasive Therapy & Allied Technologies
MITAT. Minimally invasive therapy & allied technologies

Purpose: This study aims to evaluate the accuracy of point-based registration (PBR) when used for augmented reality (AR) in laparoscopic liver resection surgery. Material and methods: The study was conducted in three different scenarios in which the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1aa9252315539fafeaad0c6bb44ac161