Zobrazeno 1 - 10
of 181
pro vyhledávání: '"Peter H. N. De With"'
Autor:
Geke Litjens, Joris P. E. A. Broekmans, Tim Boers, Marco Caballo, Maud H. F. van den Hurk, Dilek Ozdemir, Caroline J. van Schaik, Markus H. A. Janse, Erwin J. M. van Geenen, Cees J. H. M. van Laarhoven, Mathias Prokop, Peter H. N. de With, Fons van der Sommen, John J. Hermans
Publikováno v:
Diagnostics, Vol 13, Iss 20, p 3198 (2023)
The preoperative prediction of resectability pancreatic ductal adenocarcinoma (PDAC) is challenging. This retrospective single-center study examined tumor and vessel radiomics to predict the resectability of PDAC in chemo-naïve patients. The tumor a
Externí odkaz:
https://doaj.org/article/613dd6d9f9df4eaaad2aa88fc6f162ce
Autor:
Francesca Manni, Marco Mamprin, Ronald Holthuizen, Caifeng Shan, Gustav Burström, Adrian Elmi-Terander, Erik Edström, Svitlana Zinger, Peter H. N. de With
Publikováno v:
BioMedical Engineering OnLine, Vol 20, Iss 1, Pp 1-15 (2021)
Abstract Background Minimally invasive spine surgery is dependent on accurate navigation. Computer-assisted navigation is increasingly used in minimally invasive surgery (MIS), but current solutions require the use of reference markers in the surgica
Externí odkaz:
https://doaj.org/article/4f0d7c86642744cd8b70797b677e9816
Publikováno v:
IEEE Access, Vol 8, Pp 169444-169455 (2020)
Encoder-decoder networks have become the standard solution for a variety of segmentation tasks. Many of these approaches use a symmetrical design where both the encoder as well as the decoder are approximately of the same computational complexity. Ho
Externí odkaz:
https://doaj.org/article/72fe75a4fcd841e9916bb75d67d90ad2
Autor:
Ricardo R. Lopes, Marco Mamprin, Jo M. Zelis, Pim A. L. Tonino, Martijn S. van Mourik, Marije M. Vis, Svitlana Zinger, Bas A. J. M. de Mol, Peter H. N. de With, Henk A. Marquering
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 8 (2021)
Background: Machine learning models have been developed for numerous medical prognostic purposes. These models are commonly developed using data from single centers or regional registries. Including data from multiple centers improves robustness and
Externí odkaz:
https://doaj.org/article/da14c3b27e7547969392b4a11ffd1ef0
Autor:
Shoujun Huo, Yue Sun, Qinghua Guo, Tao Tan, J. Elizabeth Bolhuis, Piter Bijma, Peter H. N. de With
Publikováno v:
Foods, Vol 12, Iss 1, p 84 (2022)
In livestock breeding, continuous and objective monitoring of animals is manually unfeasible due to the large scale of breeding and expensive labour. Computer vision technology can generate accurate and real-time individual animal or animal group inf
Externí odkaz:
https://doaj.org/article/1b588ff1bd114f0d9e4e0787095553e0
Autor:
Marco Lai, Simon Skyrman, Flip Kor, Robert Homan, Victor Gabriel El-Hajj, Drazenko Babic, Erik Edström, Adrian Elmi-Terander, Benno H. W. Hendriks, Peter H. N. de With
Publikováno v:
Bioengineering, Vol 9, Iss 10, p 537 (2022)
Background: Neurosurgical procedures are complex and require years of training and experience. Traditional training on human cadavers is expensive, requires facilities and planning, and raises ethical concerns. Therefore, the use of anthropomorphic p
Externí odkaz:
https://doaj.org/article/db16c1ccd91c4874b78e98c1f60b720f
Publikováno v:
Sensors, Vol 21, Iss 14, p 4659 (2021)
This paper presents a camera-based vessel-speed enforcement system based on two cameras. The proposed system detects and tracks vessels per camera view and employs a re-identification (re-ID) function for linking vessels between the two cameras based
Externí odkaz:
https://doaj.org/article/73ecae4d2f8e46b29a87605baa432469
Autor:
Marco Mamprin, Ricardo R. Lopes, Jo M. Zelis, Pim A. L. Tonino, Martijn S. van Mourik, Marije M. Vis, Svitlana Zinger, Bas A. J. M. de Mol, Peter H. N. de With
Publikováno v:
Journal of Cardiovascular Development and Disease, Vol 8, Iss 6, p 65 (2021)
Current prognostic risk scores for transcatheter aortic valve implantation (TAVI) do not benefit yet from modern machine learning techniques, which can improve risk stratification of one-year mortality of patients before TAVI. Despite the advancement
Externí odkaz:
https://doaj.org/article/f4802f47d76d42608699bcc9b3bcddb5
Publikováno v:
Bioengineering, Vol 8, Iss 2, p 22 (2021)
Current prognostic risk scores in cardiac surgery do not benefit yet from machine learning (ML). This research aims to create a machine learning model to predict one-year mortality of a patient after transcatheter aortic valve implantation (TAVI). We
Externí odkaz:
https://doaj.org/article/bc546231ead54eddb7ea2f249738fd30
Autor:
Francesca Manni, Fons van der Sommen, Himar Fabelo, Svitlana Zinger, Caifeng Shan, Erik Edström, Adrian Elmi-Terander, Samuel Ortega, Gustavo Marrero Callicó, Peter H. N. de With
Publikováno v:
Sensors, Vol 20, Iss 23, p 6955 (2020)
The primary treatment for malignant brain tumors is surgical resection. While gross total resection improves the prognosis, a supratotal resection may result in neurological deficits. On the other hand, accurate intraoperative identification of the t
Externí odkaz:
https://doaj.org/article/fa472dd2a1004f05a77bde6668458b59