van Ginneken, Bram

Ridge-based vessel segmentation in color images of the retina

Staal, J., Abramoff, M. D., Niemeijer, M., Viergever, M. A., & van Ginneken, B. (2004) · IEEE Transactions on Medical Imaging

Retinal Imaging and AnalysisMedical Image Segmentation Techniques

Cited by 4,202

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2019) · arXiv

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2023) · Medical Image Analysis

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

The Medical Segmentation Decathlon

Antonelli, M., Reinke, A., Bakas, S., Farahani, K., Kopp-Schneider, A., Landman, B. A., Litjens, G., Menze, B., Ronneberger, O., Summers, R. M., et al. (2022) · Nature Communications

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 1,384

Evaluation of prostate segmentation algorithms for mri: The promise12 challenge

Litjens, G., Toth, R., van de Ven, W., Hoeks, C., Kerkstra, S., van Ginneken, B., Vincent, G., Guillard, G., Birbeck, N., Zhang, J., et al. (2014) · Medical Image Analysis

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 857

From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge

Bandi, P., Geessink, O., Manson, Q., Van Dijk, M., Balkenhol, M., Hermsen, M., Ehteshami Bejnordi, B., Lee, B., Paeng, K., Zhong, A., et al. (2019) · IEEE Transactions on Medical Imaging

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 569

Automated measurement of fetal head circumference using 2D ultrasound images

van den Heuvel, T. L. A., de Bruijn, D., de Korte, C. L., & Ginneken, B. V. (2018) · PLOS ONE

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 280

Automatic Calcium Scoring in Low-Dose Chest CT Using Deep Neural Networks With Dilated Convolutions

Lessmann, N., van Ginneken, B., Zreik, M., de Jong, P. A., de Vos, B. D., Viergever, M. A., & Isgum, I. (2018) · IEEE Transactions on Medical Imaging

Cardiac Imaging and DiagnosticsCOVID-19 diagnosis using AI

Cited by 263

Understanding metric-related pitfalls in image analysis validation

Reinke, A., Tizabi, M. D., Baumgartner, M., Eisenmann, M., Heckmann-Nötzel, D., Kavur, A. E., Rädsch, T., Sudre, C. H., Acion, L., Antonelli, M., et al. (2024) · Nature Methods

Cell Image Analysis TechniquesMedical Image Segmentation Techniques

Cited by 241

An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information

Melendez, J., Sánchez, C. I., Philipsen, R. H. H. M., Maduskar, P., Dawson, R., Theron, G., Dheda, K., & van Ginneken, B. (2016) · Scientific Reports

Tuberculosis Research and EpidemiologyCOVID-19 diagnosis using AI

Cited by 152

Common Limitations of Image Processing Metrics: A Picture Story

Reinke, A., Tizabi, M. D., Sudre, C. H., Eisenmann, M., Rädsch, T., Baumgartner, M., Acion, L., Antonelli, M., Arbel, T., Bakas, S., et al. (2021) · arXiv

Medical Image Segmentation TechniquesCell Image Analysis Techniques

Cited by 126

Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system

Murphy, K., Habib, S. S., Zaidi, S. M. A., Khowaja, S., Khan, A., Melendez, J., Scholten, E. T., Amad, F., Schalekamp, S., Verhagen, M., et al. (2020) · Scientific Reports

COVID-19 diagnosis using AITuberculosis Research and Epidemiology

Cited by 122

Diagnostic Accuracy of Computer-Aided Detection of Pulmonary Tuberculosis in Chest Radiographs: A Validation Study from Sub-Saharan Africa

Breuninger, M., van Ginneken, B., Philipsen, R. H. H. M., Mhimbira, F., Hella, J. J., Lwilla, F., van den Hombergh, J., Ross, A., Jugheli, L., Wagner, D., et al. (2014) · PLoS ONE

Tuberculosis Research and EpidemiologyCOVID-19 diagnosis using AI

Cited by 101

The Sensitivity and Specificity of Using a Computer Aided Diagnosis Program for Automatically Scoring Chest X-Rays of Presumptive TB Patients Compared with Xpert MTB/RIF in Lusaka Zambia

Muyoyeta, M., Maduskar, P., Moyo, M., Kasese, N., Milimo, D., Spooner, R., Kapata, N., Hogeweg, L., van Ginneken, B., & Ayles, H. (2014) · PLoS ONE

Tuberculosis Research and EpidemiologyCOVID-19 diagnosis using AI

Cited by 98

Detection of tuberculosis using digital chest radiography: automated reading vs. interpretation by clinical officers

Maduskar, P., Muyoyeta, M., Ayles, H., Hogeweg, L., Peters-Bax, L., & van Ginneken, B. (2013) · The International Journal of Tuberculosis and Lung Disease

Tuberculosis Research and EpidemiologyAI in cancer detection

Cited by 77

Automated chest-radiography as a triage for Xpert testing in resource-constrained settings: a prospective study of diagnostic accuracy and costs

Philipsen, R. H. H. M., Sánchez, C. I., Maduskar, P., Melendez, J., Peters-Bax, L., Peter, J. G., Dawson, R., Theron, G., Dheda, K., & van Ginneken, B. (2015) · Scientific Reports

Tuberculosis Research and EpidemiologyInfectious Diseases and Tuberculosis

Cited by 77

Cost-effectiveness of artificial intelligence aided vessel occlusion detection in acute stroke: an early health technology assessment

van Leeuwen, K. G., Meijer, F. J. A., Schalekamp, S., Rutten, M. J. C. M., van Dijk, E. J., van Ginneken, B., Govers, T. M., & de Rooij, M. (2021) · Insights into Imaging

Health Systems, Economic Evaluations, Quality of LifeAcute Ischemic Stroke Management

Cited by 70

Metrics reloaded: Recommendations for image analysis validation

Maier-Hein, L., Reinke, A., Godau, P., Tizabi, M. D., Buettner, F., Christodoulou, E., Glocker, B., Isensee, F., Kleesiek, J., Kozubek, M., et al. (2022) · arXiv

Cell Image Analysis TechniquesMedical Image Segmentation Techniques

Cited by 59

Reducing inter-observer variability and interaction time of MR liver volumetry by combining automatic CNN-based liver segmentation and manual corrections

Chlebus, G., Meine, H., Thoduka, S., Abolmaali, N., van Ginneken, B., Hahn, H. K., & Schenk, A. (2019) · PLOS ONE

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 56

Sex Differences in Coronary Artery and Thoracic Aorta Calcification and Their Association With Cardiovascular Mortality in Heavy Smokers

Lessmann, N., de Jong, P. A., Celeng, C., Takx, R. A. P., Viergever, M. A., van Ginneken, B., & Išgum, I. (2019) · JACC: Cardiovascular Imaging

Cardiac Imaging and DiagnosticsMedical Imaging and Pathology Studies

Cited by 49

Automatic versus human reading of chest X-rays in the Zambia National Tuberculosis Prevalence Survey

Melendez, J., Philipsen, R. H. H. M., Chanda-Kapata, P., Sunkutu, V., Kapata, N., & van Ginneken, B. (2017) · The International Journal of Tuberculosis and Lung Disease

Tuberculosis Research and EpidemiologyCOVID-19 diagnosis using AI

Cited by 36

Computer-assisted chest radiography reading for tuberculosis screening in people living with diabetes mellitus

Koesoemadinata, R. C., Kranzer, K., Livia, R., Susilawati, N., Annisa, J., Soetedjo, N. N. M., Ruslami, R., Philipsen, R., van Ginneken, B., Soetikno, R. D., et al. (2018) · The International Journal of Tuberculosis and Lung Disease

Tuberculosis Research and EpidemiologyAI in cancer detection

Cited by 35

Automatic Placenta Localization From Ultrasound Imaging in a Resource-Limited Setting Using a Predefined Ultrasound Acquisition Protocol and Deep Learning

Schilpzand, M., Neff, C., van Dillen, J., van Ginneken, B., Heskes, T., de Korte, C., & van den Heuvel, T. (2022) · Ultrasound in Medicine & Biology

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 23

Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images

van Eekelen, L., Spronck, J., Looijen-Salamon, M., Vos, S., Munari, E., Girolami, I., Eccher, A., Acs, B., Boyaci, C., de Souza, G. S., et al. (2024) · Scientific Reports

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 21