Peter M. A. van Ooijen
University Medical Center Groningen
Imaging phantomRadiologyMagnetic resonance imagingArtificial intelligenceTomographyLung cancerLung cancer screeningLungCoronary artery diseaseCoronary arteriesNodule (medicine)NeuroradiologyAngiographyNuclear medicineComputer visionComputer scienceComputed tomographyMedicineConvolutional neural networkSegmentation
106Publications
23H-index
2,662Citations
Publications 108
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#1Romke Rozema (UMCG: University Medical Center Groningen)H-Index: 1
#2Herbert T. Kruitbosch (CIT: Center for Information Technology)H-Index: 1
Last. Peter M. A. van Ooijen (UMCG: University Medical Center Groningen)H-Index: 23
view all 6 authors...
Abstract Objectives To quantitatively assess the image quality of advanced modeled iterative reconstruction and the PixelShineTM deep learning algorithm for the optimization of low dose CT protocols in midfacial trauma. Study Design A total of six fresh frozen human cadaver head specimens were CT scanned using both standard and low dose scan protocols. Varying iterative reconstruction strengths were applied to reconstruct bone and soft tissue datasets and these were subsequently applied to a dee...
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#1Ricardo Rivas (UMCG: University Medical Center Groningen)H-Index: 1
#2Rudy B Hijlkema (UG: University of Groningen)
Last. Peter M. A. van Ooijen (UMCG: University Medical Center Groningen)H-Index: 23
view all 6 authors...
Purpose null To study the effects of the control temperature, ablation time, and the background tissue surrounding the tumor on the size of the ablation zone on radiofrequency ablation (RFA) of osteoid osteoma (OO). null Materials and methods null Finite element models of non-cooled temperature-controlled RFA of typical OOs were developed to determine the resulting ablation radius at control temperatures of 70, 80, and 90°C. Three different geometries were used, mimicking common cases of OO. The...
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#1Bingjiang QiuH-Index: 3
#2Hylke van der Wel (UG: University of Groningen)H-Index: 2
Last. Peter M. A. van OoijenH-Index: 23
view all 8 authors...
Medical imaging techniques, such as (cone beam) computed tomography and magnetic resonance imaging, have proven to be a valuable component for oral and maxillofacial surgery (OMFS). Accurate segmentation of the mandible from head and neck (H&N) scans is an important step in order to build a personalized 3D digital mandible model for 3D printing and treatment planning of OMFS. Segmented mandible structures are used to effectively visualize the mandible volumes and to evaluate particular mandible ...
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Accurate segmentation of the mandible from cone-beam computed tomography (CBCT) scans is an important step for building a personalized 3D digital mandible model for maxillofacial surgery and orthodontic treatment planning because of the low radiation dose and short scanning duration. CBCT images, however, exhibit lower contrast and higher levels of noise and artifacts due to extremely low radiation in comparison with the conventional computed tomography (CT), which makes automatic mandible segme...
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To evaluate the performance of a novel convolutional neural network (CNN) for the classification of typical perifissural nodules (PFN). Chest CT data from two centers in the UK and The Netherlands (1668 unique nodules, 1260 individuals) were collected. Pulmonary nodules were classified into subtypes, including “typical PFNs” on-site, and were reviewed by a central clinician. The dataset was divided into a training/cross-validation set of 1557 nodules (1103 individuals) and a test set of 196 nodu...
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#1Bingjiang Qiu (UMCG: University Medical Center Groningen)H-Index: 3
#2Jiapan Guo (UMCG: University Medical Center Groningen)H-Index: 6
Last. Peter M. A. van Ooijen (UMCG: University Medical Center Groningen)H-Index: 23
view all 8 authors...
PURPOSE Classic encoder-decoder-based convolutional neural network (EDCNN) approaches cannot accurately segment detailed anatomical structures of the mandible in computed tomography (CT), for instance, condyles and coronoids of the mandible, which are often affected by noise and metal artifacts. The main reason is that EDCNN approaches ignore the anatomical connectivity of the organs. In this paper, we propose a novel CNN-based 3D mandible segmentation approach that has the ability to accurately...
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#1Peter A J Pijpker (UMCG: University Medical Center Groningen)H-Index: 3
#2Tim S. Oosterhuis (UMCG: University Medical Center Groningen)
Last. Joep Kraeima (UMCG: University Medical Center Groningen)H-Index: 12
view all 9 authors...
PURPOSE The purpose of this paper is to present and validate a new semi-automated 3D surface mesh segmentation approach that optimizes the laborious individual human vertebrae separation in the spinal virtual surgical planning workflow and make a direct accuracy and segmentation time comparison with current standard segmentation method. METHODS The proposed semi-automatic method uses the 3D bone surface derived from CT image data for seed point-based 3D mesh partitioning. The accuracy of the pro...
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Accurate mandible segmentation is significant in the field of maxillofacial surgery to guide clinical diagnosis and treatment and develop appropriate surgical plans. In particular, cone-beam computed tomography (CBCT) images with metal parts, such as those used in oral and maxillofacial surgery (OMFS), often have susceptibilities when metal artifacts are present such as weak and blurred boundaries caused by a high-attenuation material and a low radiation dose in image acquisition. To overcome th...
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To investigate the association of pericoronary adipose tissue mean attenuation (PCATMA) with coronary artery disease (CAD) characteristics on coronary computed tomography angiography (CCTA). We retrospectively investigated 165 symptomatic patients who underwent third-generation dual-source CCTA at 70kVp: 93 with and 72 without CAD (204 arteries with plaque, 291 without plaque). CCTA was evaluated for presence and characteristics of CAD per artery. PCATMA was measured proximally and across the mo...
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