Search Results - "Vente, Coen de"

Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-Parametric MRI by Vente, Coen de, Vos, Pieter, Hosseinzadeh, Matin, Pluim, Josien, Veta, Mitko

“…One of the most common types of cancer in men is prostate cancer (PCa). Biopsies guided by bi-parametric magnetic resonance imaging (MRI) can aid PCa…”
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Characteristics of a Large, Labeled Data Set for the Training of Artificial Intelligence for Glaucoma Screening with Fundus Photographs by Lemij, Hans G., Vente, Coen de, Sánchez, Clara I., Vermeer, Koen A.

“…Significant visual impairment due to glaucoma is largely caused by the disease being detected too late. To build a labeled data set for training artificial…”
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Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence by Lessmann, Nikolas, Sánchez, Clara I, Beenen, Ludo, Boulogne, Luuk H, Brink, Monique, Calli, Erdi, Charbonnier, Jean-Paul, Dofferhoff, Ton, van Everdingen, Wouter M, Gerke, Paul K, Geurts, Bram, Gietema, Hester A, Groeneveld, Miriam, van Harten, Louis, Hendrix, Nils, Hendrix, Ward, Huisman, Henkjan J, Išgum, Ivana, Jacobs, Colin, Kluge, Ruben, Kok, Michel, Krdzalic, Jasenko, Lassen-Schmidt, Bianca, van Leeuwen, Kicky, Meakin, James, Overkamp, Mike, van Rees Vellinga, Tjalco, van Rikxoort, Eva M, Samperna, Riccardo, Schaefer-Prokop, Cornelia, Schalekamp, Steven, Scholten, Ernst Th, Sital, Cheryl, Stöger, J Lauran, Teuwen, Jonas, Venkadesh, Kiran Vaidhya, de Vente, Coen, Vermaat, Marieke, Xie, Weiyi, de Wilde, Bram, Prokop, Mathias, van Ginneken, Bram

“…Background The coronavirus disease 2019 (COVID-19) pandemic has spread across the globe with alarming speed, morbidity, and mortality. Immediate triage of…”
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AIROGS: Artificial Intelligence for Robust Glaucoma Screening Challenge by de Vente, Coen, Vermeer, Koenraad A., Jaccard, Nicolas, Wang, He, Sun, Hongyi, Khader, Firas, Truhn, Daniel, Aimyshev, Temirgali, Zhanibekuly, Yerkebulan, Le, Tien-Dung, Galdran, Adrian, Ballester, Miguel Angel Gonzalez, Carneiro, Gustavo, Devika, R. G., Sethumadhavan, Hrishikesh Panikkasseril, Puthussery, Densen, Liu, Hong, Yang, Zekang, Kondo, Satoshi, Kasai, Satoshi, Wang, Edward, Durvasula, Ashritha, Heras, Jonathan, Zapata, Miguel Angel, Araujo, Teresa, Aresta, Guilherme, Bogunovic, Hrvoje, Arikan, Mustafa, Lee, Yeong Chan, Cho, Hyun Bin, Choi, Yoon Ho, Qayyum, Abdul, Razzak, Imran, van Ginneken, Bram, Lemij, Hans G., Sanchez, Clara I.

“…The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs…”
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Automated COVID-19 Grading With Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison by Vente, Coen de, Boulogne, Luuk H., Venkadesh, Kiran Vaidhya, Sital, Cheryl, Lessmann, Nikolas, Jacobs, Colin, Sanchez, Clara I., Ginneken, Bram van

“…Amidst the ongoing pandemic, the assessment of computed tomography (CT) images for COVID-19 presence can exceed the workload capacity of radiologists. Several…”
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A deep learning framework for the detection and quantification of drusen and reticular pseudodrusen on optical coherence tomography by Schwartz, Roy, Khalid, Hagar, Liakopoulos, Sandra, Ouyang, Yanling, de Vente, Coen, González-Gonzalo, Cristina, Lee, Aaron Y, Guymer, Robyn, Chew, Emily Y, Egan, Catherine, Wu, Zhichao, Kumar, Himeesh, Farrington, Joseph, Sánchez, Clara I, Tufail, Adnan

“…Purpose - To develop and validate a deep learning (DL) framework for the detection and quantification of drusen and reticular pseudodrusen (RPD) on optical…”
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A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging by Xiong, Zhaohan, Xia, Qing, Hu, Zhiqiang, Huang, Ning, Bian, Cheng, Zheng, Yefeng, Vesal, Sulaiman, Ravikumar, Nishant, Maier, Andreas, Yang, Xin, Heng, Pheng-Ann, Ni, Dong, Li, Caizi, Tong, Qianqian, Si, Weixin, Puybareau, Elodie, Khoudli, Younes, Géraud, Thierry, Chen, Chen, Bai, Wenjia, Rueckert, Daniel, Xu, Lingchao, Zhuang, Xiahai, Luo, Xinzhe, Jia, Shuman, Sermesant, Maxime, Liu, Yashu, Wang, Kuanquan, Borra, Davide, Masci, Alessandro, Corsi, Cristiana, de Vente, Coen, Veta, Mitko, Karim, Rashed, Preetha, Chandrakanth Jayachandran, Engelhardt, Sandy, Qiao, Menyun, Wang, Yuanyuan, Tao, Qian, Nuñez-Garcia, Marta, Camara, Oscar, Savioli, Nicolo, Lamata, Pablo, Zhao, Jichao

“…•A benchmark study of a global segmentation challenge conducted on the largest atrial LGE-MRI dataset.•Performed rigorous subgroup analysis and hyper-parameter…”
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Uncertainty-aware multiple-instance learning for reliable classification: Application to optical coherence tomography by de Vente, Coen, van Ginneken, Bram, Hoyng, Carel B., Klaver, Caroline C.W., Sánchez, Clara I.

“…Deep learning classification models for medical image analysis often perform well on data from scanners that were used to acquire the training data. However,…”
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A Deep Learning Framework for the Detection and Quantification of Reticular Pseudodrusen and Drusen on Optical Coherence Tomography by Schwartz, Roy, Khalid, Hagar, Liakopoulos, Sandra, Ouyang, Yanling, de Vente, Coen, González-Gonzalo, Cristina, Lee, Aaron Y, Guymer, Robyn, Chew, Emily Y, Egan, Catherine, Wu, Zhichao, Kumar, Himeesh, Farrington, Joseph, Müller, Philipp L, Sánchez, Clara I, Tufail, Adnan

“…The purpose of this study was to develop and validate a deep learning (DL) framework for the detection and quantification of reticular pseudodrusen (RPD) and…”
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Automated Assessment of CO-RADS and Chest CT Severity Scores in Patients with Suspected COVID-19 Using Artificial Intelligence by Lessmann, Nikolas, Sánchez, Clara I., Beenen, Ludo, Boulogne, Luuk H., Brink, Monique, Calli, Erdi, Charbonnier, Jean-Paul, Dofferhoff, Ton, van Everdingen, Wouter M., Gerke, Paul K., Geurts, Bram, Gietema, Hester A., Groeneveld, Miriam, van Harten, Louis, Hendrix, Nils, Hendrix, Ward, Huisman, Henkjan J., Išgum, Ivana, Jacobs, Colin, Kluge, Ruben, Kok, Michel, Krdzalic, Jasenko, Lassen-Schmidt, Bianca, van Leeuwen, Kicky, Meakin, James, Overkamp, Mike, van Rees Vellinga, Tjalco, van Rikxoort, Eva M., Samperna, Riccardo, Schaefer-Prokop, Cornelia, Schalekamp, Steven, Scholten, Ernst Th, Sital, Cheryl, Stöger, Lauran, Teuwen, Jonas, Vaidhya Venkadesh, Kiran, de Vente, Coen, Vermaat, Marieke, Xie, Weiyi, de Wilde, Bram, Prokop, Mathias, van Ginneken, Bram

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Generalizable Deep Learning for the Detection of Incomplete and Complete Retinal Pigment Epithelium and Outer Retinal Atrophy: A MACUSTAR Report by de Vente, Coen, Valmaggia, Philippe, Hoyng, Carel B, Holz, Frank G, Islam, Mohammad M, Klaver, Caroline C W, Boon, Camiel J F, Schmitz-Valckenberg, Steffen, Tufail, Adnan, Saßmannshausen, Marlene, Sánchez, Clara I

“…The purpose of this study was to develop a deep learning algorithm for detecting and quantifying incomplete retinal pigment epithelium and outer retinal…”
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Conditioning 3D Diffusion Models with 2D Images: Towards Standardized OCT Volumes through En Face-Informed Super-Resolution by de Vente, Coen, Islam, Mohammad Mohaiminul, Valmaggia, Philippe, Hoyng, Carel, Tufail, Adnan, Sánchez, Clara I

“…High anisotropy in volumetric medical images can lead to the inconsistent quantification of anatomical and pathological structures. Particularly in optical…”
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Uncertainty-Aware Multiple-Instance Learning for Reliable Classification: Application to Optical Coherence Tomography by de Vente, Coen, van Ginneken, Bram, Hoyng, Carel B, Klaver, Caroline C. W, Sánchez, Clara I

“…Deep learning classification models for medical image analysis often perform well on data from scanners that were used during training. However, when these…”
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Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study by de Vente, Coen, Boulogne, Luuk H, Venkadesh, Kiran Vaidhya, Sital, Cheryl, Lessmann, Nikolas, Jacobs, Colin, Sánchez, Clara I, van Ginneken, Bram

“…Amidst the ongoing pandemic, several studies have shown that COVID-19 classification and grading using computed tomography (CT) images can be automated with…”
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AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge by de Vente, Coen, Vermeer, Koenraad A, Jaccard, Nicolas, Wang, He, Sun, Hongyi, Khader, Firas, Truhn, Daniel, Aimyshev, Temirgali, Zhanibekuly, Yerkebulan, Le, Tien-Dung, Galdran, Adrian, Ballester, Miguel Ángel González, Carneiro, Gustavo, G, Devika R, S, Hrishikesh P, Puthussery, Densen, Liu, Hong, Yang, Zekang, Kondo, Satoshi, Kasai, Satoshi, Wang, Edward, Durvasula, Ashritha, Heras, Jónathan, Zapata, Miguel Ángel, Araújo, Teresa, Aresta, Guilherme, Bogunović, Hrvoje, Arikan, Mustafa, Lee, Yeong Chan, Cho, Hyun Bin, Choi, Yoon Ho, Qayyum, Abdul, Razzak, Imran, van Ginneken, Bram, Lemij, Hans G, Sánchez, Clara I

“…The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs…”
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A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging by Xiong, Zhaohan, Xia, Qing, Hu, Zhiqiang, Huang, Ning, Bian, Cheng, Zheng, Yefeng, Vesal, Sulaiman, Ravikumar, Nishant, Maier, Andreas, Yang, Xin, Heng, Pheng-Ann, Ni, Dong, Li, Caizi, Tong, Qianqian, Si, Weixin, Puybareau, Elodie, Khoudli, Younes, Geraud, Thierry, Chen, Chen, Bai, Wenjia, Rueckert, Daniel, Xu, Lingchao, Zhuang, Xiahai, Luo, Xinzhe, Jia, Shuman, Sermesant, Maxime, Liu, Yashu, Wang, Kuanquan, Borra, Davide, Masci, Alessandro, Corsi, Cristiana, de Vente, Coen, Veta, Mitko, Karim, Rashed, Preetha, Chandrakanth Jayachandran, Engelhardt, Sandy, Qiao, Menyun, Wang, Yuanyuan, Tao, Qian, Nunez-Garcia, Marta, Camara, Oscar, Savioli, Nicolo, Lamata, Pablo, Zhao, Jichao

“…Segmentation of cardiac images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) widely used for visualizing diseased cardiac…”
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