264 publications found

Publications

264 publications | 33980 citations
  • Chenouard N, Smal I, de Chaumont F, et al.. Objective comparison of particle tracking methods. Nat Methods. 2014;11(3):281-289.
  • Figueira G, Wang Y, Sun L, Zhou H, Zhang Q. Adversarial-Based Domain Adaptation Networks for Unsupervised Tumour Detection in Histopathology. 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). Published online April 2020:1284-1288.
  • Maier O, Menze BH, von der Gablentz J, et al.. ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI. Medical Image Analysis. 2017;35:250-269.
  • Chen Q, Xu X, Hu S, Li X, Zou Q, Li Y. A transfer learning approach for classification of clinical significant prostate cancers from mpMRI scans. Armato SG, Petrick NA, eds.. SPIE Proceedings. 2017;10134:101344F.
  • Sreekumar A, Nair KR, Sudheer S, Ganesh Nayar H, Nair JJ. Malignant Lung Nodule Detection using Deep Learning. 2020 International Conference on Communication and Signal Processing (ICCSP). Published online July 2020:0209-0212.
  • Hameeteman K, Zuluaga MA, Freiman M, et al.. Evaluation framework for carotid bifurcation lumen segmentation and stenosis grading. Medical Image Analysis. 2011;15(4):477-488.
  • Charbonnier J-P, Brink M, Ciompi F, Scholten ET, Schaefer-Prokop CM, van Rikxoort EM. Automatic Pulmonary Artery-Vein Separation and Classification in Computed Tomography Using Tree Partitioning and Peripheral Vessel Matching. IEEE Trans Med Imaging. 2016;35(3):882-892.
  • Meijering E, Carpenter AE, Peng H, Hamprecht FA, Olivo-Marin J-C. Imagining the future of bioimage analysis. Nat Biotechnol. 2016;34(12):1250-1255.
  • Swiderska-Chadaj Z, Pinckaers H, van Rijthoven M, et al.. Learning to detect lymphocytes in immunohistochemistry with deep learning. Medical Image Analysis. 2019;58:101547.
  • Marstal K, Berendsen F, Dekker N, Staring M, Klein S. The Continuous Registration Challenge: Evaluation-as-a-Service for Medical Image Registration Algorithms. 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019). Published online April 2019:1399-1402.
  • Banerjee N, Sathish R, Sheet D. Deep Neural Architecture for Localization and Tracking of Surgical Tools in Cataract Surgery. Lecture Notes in Computational Vision and Biomechanics. Published online 2019:31-38.
  • Bandi P, Geessink O, Manson Q, et al.. From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge. IEEE Trans Med Imaging. 2019;38(2):550-560.
    CAMELYON17 Tumor Detection in Lymph Nodes
  • Fan K, Wen S, Deng Z. Deep Learning for Detecting Breast Cancer Metastases on WSI. Smart Innovation, Systems and Technologies. Published online 2019:137-145.
  • Laxmisagar HS, Hanumantharaju MC. A Survey on Automated Detection of Breast Cancer based Histopathology Images. 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA). Published online March 2020:19-24.
  • Armato SG III, Drukker K, Li F, et al.. LUNGx Challenge for computerized lung nodule classification. J Med Imag. 2016;3(4):044506.
  • Zheng X, Sun L, Wang Y, Ding L, Duan Y. Multi-class breast tumor region detection for gigapixel pathology images using deep neural network with rescale approach. Yu H, Pu Y, Li C, Pan Z, eds.. Tenth International Conference on Graphics and Image Processing (ICGIP 2018). Published online May 6, 2019:29.
  • Zhong Z, Li J, Zhang Z, Jiao Z, Gao X. A Coarse-to-Fine Deep Heatmap Regression Method for Adolescent Idiopathic Scoliosis Assessment. Lecture Notes in Computer Science. Published online 2020:101-106.
  • Katz O, Presil D, Cohen L, Schwartzbard Y, Hoch S, Kashani S. Pulmonary-Nodule Detection Using an Ensemble of 3D SE-ResNet18 and DPN68 Models. Lecture Notes in Computer Science. Published online 2020:378-385.
  • Brancati N, Frucci M, Riccio D. Multi-classification of Breast Cancer Histology Images by Using a Fine-Tuning Strategy. Lecture Notes in Computer Science. Published online 2018:771-778.
  • Bron E. Large-scale objective comparison of 29 novel algorithms for computer-aided diagnosis of dementia based on structural MRI. European Congress of Radiology. Published online 2015.
  • Mahbod A, Ellinger I, Ecker R, Smedby Ö, Wang C. Breast Cancer Histological Image Classification Using Fine-Tuned Deep Network Fusion. Lecture Notes in Computer Science. Published online 2018:754-762.
  • Wang Y, Sun L, Ma K, Fang J. Breast Cancer Microscope Image Classification Based on CNN with Image Deformation. Lecture Notes in Computer Science. Published online 2018:845-852.
  • Cao H, Bernard S, Heutte L, Sabourin R. Improve the Performance of Transfer Learning Without Fine-Tuning Using Dissimilarity-Based Multi-view Learning for Breast Cancer Histology Images. Lecture Notes in Computer Science. Published online 2018:779-787.
  • Armato SG III, Hadjiiski L, Tourassi GD, et al.. Guest Editorial: LUNGx Challenge for computerized lung nodule classification: reflections and lessons learned. J Med Imag. 2015;2(2):020103.
  • Nazeri K, Aminpour A, Ebrahimi M. Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification. Lecture Notes in Computer Science. Published online 2018:717-726.
  • Kwok S. Multiclass Classification of Breast Cancer in Whole-Slide Images. Lecture Notes in Computer Science. Published online 2018:931-940.
  • Grob D, Ginneken B van, Oostveen L, Prokop M, Brink M, Sechopoulos I. [OA136] The lumic challenge: How accurate are registration algorithms in registering lung CT images for subtraction?. Physica Medica. 2018;52:52.
  • Rakhlin A, Shvets A, Iglovikov V, Kalinin AA. Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis. Lecture Notes in Computer Science. Published online 2018:737-744.
  • Bernal J, Tajkbaksh N, Sanchez FJ, et al.. Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results From the MICCAI 2015 Endoscopic Vision Challenge. IEEE Trans Med Imaging. 2017;36(6):1231-1249.
  • Karim R, Housden RJ, Balasubramaniam M, et al.. Evaluation of current algorithms for segmentation of scar tissue from late Gadolinium enhancement cardiovascular magnetic resonance of the left atrium: an open-access grand challenge. Journal of Cardiovascular Magnetic Resonance. 2013;15(1):105.
  • Verma R, Kumar N, Abhijeet Patil, Kurian NC, Swapnil Rane, Sethi A. Multi-organ Nuclei Segmentation and Classification Challenge 2020. Unpublished. Published online 2020.
    MoNuSAC-2020
  • Lo P, van Ginneken B, Reinhardt JM, et al.. Extraction of Airways From CT (EXACT'09). IEEE Trans Med Imaging. 2012;31(11):2093-2107.
  • Xiao Y, Rivaz H, Chabanas M, et al.. Evaluation of MRI to Ultrasound Registration Methods for Brain Shift Correction: The CuRIOUS2018 Challenge. IEEE Trans Med Imaging. 2020;39(3):777-786.
    curious2018
  • Murphy K, van Ginneken B, Reinhardt JM, et al.. Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge. IEEE Trans Med Imaging. 2011;30(11):1901-1920.
    EMPIRE10
  • Heimann T, van Ginneken B, Styner MA, et al.. Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets. IEEE Trans Med Imaging. 2009;28(8):1251-1265.
    SLIVER07
  • Bogunovic H, Venhuizen F, Klimscha S, et al.. RETOUCH: The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge. IEEE Trans Med Imaging. 2019;38(8):1858-1874.
    RETOUCH
  • van Ginneken B, Jacobs C. LUNA16 Part 2/2. Published online March 17, 2019.
  • CADA Challenge Organizers. CADA Test Dataset, original image data. Published online August 4, 2020.
  • CADA Challenge Organizers. CADA Test Dataset Addon for Task 3: Vessel and Aneurysm Masks/Geometries. Published online August 29, 2020.
  • CADA Challenge Organizers. CADA Training Dataset, Part 2 (Add-On for Task 3). Published online August 26, 2020.
  • Hering A, Murphy K, van Ginneken B. Learn2Reg Challenge: CT Lung Registration - Training Data. Published online May 20, 2020.
    Learn2Reg
  • CADA Challenge Organizers. CADA Test Dataset addon for task 2 (segmentation): Aneurysm seed points. Published online August 22, 2020.
  • CADA Challenge Organizers. CADA Training Dataset, image and geometry data. Published online July 24, 2020.
  • Francesco Ciompi, Yiping Jiao, Jeroen van der Laak. Lymphocyte Assessment Hackathon (LYSTO). Published online October 4, 2019.
  • van Ginneken B, Jacobs C. LUNA16 Part 1/2. Published online March 16, 2019.
  • Polónia A, Eloy C, Aguiar P. BACH Dataset : Grand Challenge on Breast Cancer Histology images. Published online May 31, 2019.
  • Swiderska-Chadaj Z, Ciompi F. LYON19- Lymphocyte Detection Test Set. Published online September 4, 2019.
  • van Ginneken B. SLIVER07. Published online March 17, 2019.
  • van Ginneken B. ANODE09. Published online December 30, 2019.
  • Heuvel TLAVD, Bruijn DD, Korte CLD, Ginneken BV. Automated measurement of fetal head circumference using 2D ultrasound images. Published online July 27, 2018.