Article
Computer Science, Information Systems
Xingyu Fu, Bin Fang, Mingliang Zhou, Sam Kwong
Summary: This paper presents a new method for image segmentation, using adaptively weighted signed pressure force and Legendre polynomial method to drive an active contour, ensuring high accuracy and computational efficiency for images with inhomogeneous intensity, blurred edges, low contrast, and noise problems.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Yunyun Yang, Ruicheng Xie, Wenjing Jia, Gang Zhao
Summary: This paper introduces a double level set segmentation model based on mutual exclusion, which accurately and independently segments adjacent regions while maintaining their independence. Experimental results demonstrate the model's high accuracy in segmenting adjacent tissues in brain, as well as its robustness to intensity inhomogeneity and noise in synthetic images. Comparisons with other models show that the double level sets model outperforms classical models in segmenting adjacent tissues.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Engineering, Biomedical
Jiahui Dong, Danni Ai, Jingfan Fan, Qiaoling Deng, Hong Song, Zhigang Cheng, Ping Liang, Yongtian Wang, Jian Yang
Summary: This paper presents a 3D tensor-based active contour model method for improving the accuracy of vessel segmentation in 3D ultrasound images, utilizing contrast-independent multiscale bottom-hat tensor representation and local-global information to effectively extract vessel boundaries from inhomogeneous and homogeneous regions. Clinical experiments show that the proposed method achieves a smoother and more accurate vessel boundary compared to competing methods, with mean SE, SP and ACC of 0.7768 +/- 0.0597, 0.9978 +/- 0.0013 and 0.9971 +/- 0.0015 respectively. Public dataset experiments demonstrate the method's ability to segment complex vessels in different medical images with noise and low contrast.
PHYSICS IN MEDICINE AND BIOLOGY
(2021)
Article
Mathematics
Noor Ain Syazwani Mohd Ghani, Abdul Kadir Jumaat, Rozi Mahmud, Mohd Azdi Maasar, Farizuwana Akma Zulkifle, Aisyah Mat Jasin
Summary: This study proposes a new variational level set model incorporating Self-Organizing Map (SOM) algorithm and Gaussian function for mammography image segmentation. Experimental results indicate that this model achieves higher segmentation accuracy and faster computational speed compared to other iterative models.
Article
Computer Science, Information Systems
Jiajie Zhu, Bin Fang, Mingliang Zhou, Futing Luo, Weizhi Xian, Gang Wang
Summary: This paper proposes an active contour model based on adaptively variable exponent combining Legendre polynomial for image segmentation. By defining Legendre polynomial intensity, adaptively LPI term, and introducing distance regularization term, the method demonstrates strong robustness and adaptability in handling intensity inhomogeneity and blurred boundaries.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Shuai Dong, Chen Chen, Yihui Liang, Kun Zou, Guisong Liu
Summary: This paper proposes a multi-task framework to address the challenge of defect detection in photovoltaic (PV) glass products. The framework uses an auxiliary semantic segmentation task to assist the main defective classification task, and introduces a new representation of contours called level set map (LSM) to further improve performance. Experimental results show that the proposed framework significantly improves the accuracy of PV glass defective detection.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Ming Dai, Zhiheng Zhou, Tianlei Wang, Yongfan Guo
Summary: In this paper, a novel segmentation model using generalized divergences is proposed based on the traditional level set method. The main advantage of generalized divergences is their smooth connection performance in measuring the discrepancy between two probability distributions of segmented image parts. Experimental results demonstrate the superior performance of the proposed method in both qualitative and quantitative aspects compared to previous active contour models.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Mathematics
Pengshuai Yin, Yupeng Fang, Qilin Wan
Summary: This paper proposes a multiscale network with dual attention for segmenting retinal blood vessels. Experimental results show that the method achieves good performance on two datasets, and the proposed architecture is simple and effective.
Article
Engineering, Biomedical
Yifei Liu, Qingtian Wu, Xueyu Liu, Junyu Lu, Zhenhuan Xu, Yongfei Wu, Shu Feng
Summary: This study proposes a method to enhance continuous edge prediction in retinal vessel segmentation through level set guidance and self-learning mechanisms. The experiments demonstrate that the method performs well in feature extraction and preserving continuous edges.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Optics
Yang Chen, Guirong Weng
Summary: This research proposes an active contour model based on local pre-piecewise fitting image, which improves robustness by optimizing the gradient descent flow formula and regularization term. It effectively segments images with uneven grayscale and has obvious advantages in initialization and segmentation efficiency.
Article
Computer Science, Information Systems
Daniel Reska, Marek Kretowski
Summary: This paper presents a fast multi-stage image segmentation method that incorporates texture analysis into a level set-based active contour framework. It allows integrating multiple feature extraction methods without the need for prior knowledge of image patterns, and achieves high performance through GPU acceleration. The method is validated on synthetic and natural images and compared with similar algorithms.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Engineering, Multidisciplinary
Xin Yan, Guirong Weng
Summary: The paper proposes a hybrid active contour model driven by optimized local pre-fitting image energy for fast image segmentation, which effectively handles images with intensity inhomogeneity and noise interference. By combining different pre-fitting functions and an optimized edge indicator function, the proposed model shows high efficiency and robustness in initializing parameters and segmenting images with various characteristics.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Computer Science, Interdisciplinary Applications
Gangming Zhao, Kongming Liang, Chengwei Pan, Fandong Zhang, Xianpeng Wu, Xinyang Hu, Yizhou Yu
Summary: In this paper, a novel hybrid deep neural network for vessel segmentation is proposed. This network consists of two cascaded subnetworks for initial and refined segmentation, and utilizes cross-network multi-scale feature fusion to achieve high-quality vessel segmentation. The graph in the second subnetwork is constructed to tackle the challenges caused by vessel sparsity and anisotropy.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)
Article
Computer Science, Artificial Intelligence
Abdelkader Birane, Latifa Hamami
Summary: A new active contour model was proposed in this research, incorporating different mathematical methods to address challenges in image segmentation. The study demonstrated that this model can effectively deal with noise and intensity inhomogeneities while ensuring segmentation accuracy.
IET IMAGE PROCESSING
(2021)
Article
Engineering, Multidisciplinary
Jianyong Li, Ge Gao, Yanhong Liu, Lei Yang
Summary: Retinal fundus images contain important morphological information, making precise segmentation of retinal vessels crucial for clinical diagnosis. DCNN-based automatic segmentation methods, such as U-Net, have been developed to replace manual labeling and reduce labor cost. However, challenges remain in fusing features effectively and preserving contextual information. To address these issues, a multiscale attention-guided fusion network, MAGF-Net, is proposed for retinal vessel segmentation.
Article
Cardiac & Cardiovascular Systems
Shuichiro Kazawa, Carlo de Asmundis, Maysam Al Housari, Gezim Bala, Juan Sieira, Dries Belsack, Johan De Mey, Stijn Lochy, Bert Vandeloo, Jean-Francois Argacha, Pedro Brugada, Gian-Battista Chierchia, Kaoru Tanaka, Erwin Stroeker
Summary: This study evaluates coronary artery disease (CAD) in atrial fibrillation (AF) patients requiring ablation using computed tomography coronary angiography (CTCA)-derived fractional flow reserve (FFR). The results showed similar prevalence of CAD in both the AF group and non-AF group, suggesting shared associated risk factors for CAD and AF.
Article
Radiology, Nuclear Medicine & Medical Imaging
Gert Van Gompel, Laurence Delombaerde, Federica Zanca, Kaoru Tanaka, Dries Belsack, Johan de Mey, Nico Buls
Summary: This study aimed to harmonize arterial enhancement in coronary CT angiography (CTA) exams by implementing a patient-, contrast- and kV-tailored injection protocol. The results showed that by using a model based on patient's fat free mass, contrast agent concentration, and CT-scan tube voltage, the arterial enhancement among patients can be adjusted to a predefined target value.
JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS
(2023)
Article
Anatomy & Morphology
Michel De Maeseneer, Seema Doering, Veerle De Grove, Nico Buls, Johan de Mey, Maryam Shahabpour, Steven Provyn, Inneke Willekens
Summary: This study aimed to compare the amount of fluid in synovial sheaths of the ankle before and after running. The results showed that the amount of fluid increased after running, suggesting that the threshold for normally acceptable fluid should be adjusted after physical activity.
SURGICAL AND RADIOLOGIC ANATOMY
(2023)
Article
Cardiac & Cardiovascular Systems
Muryo Terasawa, Gian-Battista Chierchia, Maysam Al Housari, Gezim Bala, Bernard Cosyns, Steven Droogmans, Kaoru Tanaka, Dries Belsack, Johan De Mey, Juan Sieira, Pedro Brugada, Carlo de Asmundis, Erwin Stroker
Summary: This study aims to identify predictors of individual late pulmonary vein reconnection after second-generation cryoballoon ablation. Anatomic indicators of late pulmonary vein reconnection have not been studied on an individual PV level, nor weighed against clinical and procedural factors. Clinical, procedural, and PV anatomic data were analyzed, and it was found that cardiac CT-based evaluation of anatomic PV characteristics presented higher predictive value compared to clinical and procedural variables. Pre-procedural identification of unfavorable PV anatomy might be important in tailoring the ablation approach.
EUROPEAN HEART JOURNAL-CARDIOVASCULAR IMAGING
(2023)
Article
Neurosciences
B. Tassignon, A. Radwan, J. Blommaert, L. Stas, S. D. Allard, F. De Ridder, E. De Waele, L. C. Bulnes, N. Hoornaert, P. Lacor, E. Lathouwers, R. Mertens, M. Naeyaert, H. Raeymaekers, L. Seyler, A. M. Van Binst, L. Van Imschoot, L. Van Liedekerke, J. Van Schependom, P. Van Schuerbeek, M. Vandekerckhove, R. Meeusen, S. Sunaert, G. Nagels, J. De Mey, K. De Pauw
Summary: This study evaluated the whole-brain structural connectivity and cognitive performance of COVID-19 survivors through brain scans and cognitive tests. The results showed that the adverse effects of COVID-19 on brain functioning and structure decrease over time. However, future research with larger sample sizes, matched control groups, and longer follow-up periods is needed to confirm these findings.
EXPERIMENTAL BRAIN RESEARCH
(2023)
Article
Cardiac & Cardiovascular Systems
Kai Ninomiya, Patrick W. Serruys, Scot Garg, Shinichiro Masuda, Shigetaka Kageyama, Nozomi Kotoku, Marie Angele Morel, Charles Taylor, John D. Puskas, Jagat Narula, Ulrich Schneider, Torsten Doenst, Kaoru Tanaka, Johan De Mey, Mark La Meir, Saima Mushtaq, Antonio L. Bartorelli, Giulio Pompilio, Daniele Andreini, Yoshinobu Onuma
Summary: The feasibility of using CCTA and FFRCT as guidance in the FASTTRACK CABG trial is determined by the need for invasive coronary angiography. According to the SS-2020, the first 57 patients enrolled in the trial received the appropriate revascularization modality, and the DSMB allowed the investigators to continue the study.
CARDIOVASCULAR REVASCULARIZATION MEDICINE
(2023)
Article
Biochemistry & Molecular Biology
Shigetaka Kageyama, Kaoru Tanaka, Shinichiro Masuda, Momoko Kageyama, Scot Garg, Adam Updegrove, Johan De Mey, Mark La Meir, Yoshinobu Onuma, Patrick W. Serruys
Summary: A 79-year-old male patient with chronic coronary syndrome and complex coronary artery disease was enrolled in a clinical trial assessing the use of coronary computed tomography angiography (CCTA) and CCTA-derived fractional flow reserve (FFRCT) for surgical revascularization. Discordance between CCTA and initial FFRCT results required further analysis using invasive and non-invasive coronary angiography. The findings revealed that the stenosis in the proximal left anterior descending artery (LAD) was physiologically significant in angiography-derived fractional flow reserve (FFR), while it remained functionally negative in the second assessment of FFRCT, possibly due to extensive calcification.
Article
Radiology, Nuclear Medicine & Medical Imaging
Jakub Ceranka, Frederic Lecouvet, Nicolas Michoux, Johan de Mey, Hubert Raeymaekers, Thierry Metens, Jef Vandemeulebroucke
Summary: This study tested and compared different intensity standardization approaches for whole-body multi-parametric MR images. The piecewise linear intensity standardization approach provided the best compromise between standardization accuracy and method stability. Linear piecewise approaches showed the overall best performance across multiple validation metrics, mostly because of its robustness.
BIOMEDICAL PHYSICS & ENGINEERING EXPRESS
(2023)
Correction
Multidisciplinary Sciences
Elke Lathouwers, Ahmed Radwan, Jeroen Blommaert, Lara Stas, Bruno Tassignon, Sabine D. Allard, Filip De Ridder, Elisabeth De Waele, Nicole Hoornaert, Patrick Lacor, Rembert Mertens, Maarten Naeyaert, Hubert Raeymaekers, Lucie Seyler, Anne-Marie Vanbinst, Lien Van Liedekerke, Jeroen Van Schependom, Peter Van Schuerbeek, Steven Provyn, Bart Roelands, Marie Vandekerckhove, Romain Meeusen, Stefan Sunaert, Guy Nagels, Johan De Mey, Kevin De Pauw
SCIENTIFIC REPORTS
(2023)
Article
Cardiac & Cardiovascular Systems
Shinichiro Masuda, Patrick W. Serruys, Saima Mushtaq, Kaoru Tanaka, Damien Mandry, Ronny R. Buechel, Franck Digne, Ulrich Schneider, Giulio Pompilio, Mark La Meir, Torsten Doenst, Ulf Teichgraber, Marie-Angele Morel, Nozomi Kotoku, Kai Ninomiya, Shigetaka Kageyama, Neil 'Leary, Carlos Collet, Scot Garg, Johan de Mey, Daniele Andreini, Yoshinobu Onuma
Summary: This study compared the prognostic value of invasive coronary angiography (ICA) and coronary computed tomography angiography (CCTA) in predicting long-term vital prognosis post-revascularization in patients with coronary artery disease. The results showed that the SYNTAX score II 2020 (SS-2020) derived from both ICA and CCTA had similar predictive ability and could discriminate vital prognosis in high- and low-risk patients.
JOURNAL OF CARDIOVASCULAR COMPUTED TOMOGRAPHY
(2023)
Article
Cardiac & Cardiovascular Systems
Toshimitsu Tsugu, Kaoru Tanaka, Yuji Nagatomo, Michel De Maeseneer, Johan De Mey
Summary: Fractional flow reserve derived from computed tomography decreases across severe coronary stenosis, but there can be cases where no significant changes are observed. In this report, a 75-year-old man with severe stenosis in the right coronary artery showed no significant changes in fractional flow reserve-derived from computed tomography despite the presence of severe stenotic lesion. The presence of a large acute marginal branch and significantly lower plaque components in the stenotic lesion may have influenced the results.
TURK KARDIYOLOJI DERNEGI ARSIVI-ARCHIVES OF THE TURKISH SOCIETY OF CARDIOLOGY
(2023)
Meeting Abstract
Cardiac & Cardiovascular Systems
Jean-Francois Argacha, Bert Vandeloo, Andreea Motoc, Kaoru Tanaka, Dries Belsack, Vincent Michiels, Stijn Lochy, Toshimitsu Tsugu, Eleftherios Choustoulakis, Julien Magne, Johan De Mey, Bernard Cosyns
Article
Cardiac & Cardiovascular Systems
Toshimitsu Tsugu, Kaoru Tanaka, Yuji Nagatomo, Michel De Maeseneer, Johan de Mey
Summary: Computed tomography-derived fractional flow reserve decreases from the proximal to the distal with coronary stenosis. Paradoxical changes in computed tomography-derived fractional flow reserve require unconventional vessel morphology and specific high driving force. We present a case of marked elevation of computed tomography-derived fractional flow reserve in the middle left anterior descending artery with severe coronary stenosis.
TURK KARDIYOLOJI DERNEGI ARSIVI-ARCHIVES OF THE TURKISH SOCIETY OF CARDIOLOGY
(2023)
Article
Cardiac & Cardiovascular Systems
Nozomi Kotoku, Patrick W. Serruys, Shigetaka Kageyama, Scot Garg, Shinichiro Masuda, Kai Ninomiya, Juan B. Grau, Himanshu Gupta, Vikram Agarwal, Marie-Angele Morel, Torsten Doenst, Ulrich Schneider, Kaoru Tanaka, Mark Lameir, Saima Mushtaq, Pontone Gianluca, Giulio Pompilio, Ulf Teichgraeber, John Puskas, Jagat Narula, Johan de Mey, Daniele Andreini, Yoshinobu Onuma
Summary: This study describes the updated approach of using coronary computed tomographic angiography for assessing the completeness of revascularization after coronary artery bypass graft surgery. The results show that CCTA-based coronary artery bypass graft anatomic SYNTAX Score (aSS) has good reproducibility and can be used to quantify the completeness of revascularization in CABG patients.
INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING
(2023)
Article
Cardiac & Cardiovascular Systems
Toshimitsu Tsugu, Kaoru Tanaka, Yuji Nagatomo, Michel De Maeseneer, Johan De Mey
Summary: This study examined the effects of vessel morphology on computed tomography-derived fractional flow reserve in 1492 outpatients with suspected coronary artery disease. The results showed that, even with similar vessel length and plaque characteristics, there were significant differences in lumen volume and distal computed tomography-derived fractional flow reserve between two patients, indicating that computed tomography-derived fractional flow reserve depends not only on vessel length and plaque characteristics, but also on lumen volume and vessel morphology.
TURK KARDIYOLOJI DERNEGI ARSIVI-ARCHIVES OF THE TURKISH SOCIETY OF CARDIOLOGY
(2023)