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262 publications found

• Dorsa Ziaei, Jung H, Tianyi Miao. Automation of Nuclei Identification and Counting In Colon Histology Images. Published online March 4, 2022.
• Azzuni H, Ridzuan M, Xu M, Yaqub M. Color Space-based HoVer-Net for Nuclei Instance Segmentation and Classification. arXiv. Published online March 7, 2022.
• Williams LZJ, Fitzgibbon SP, Bozek J, et al.. Structural and functional asymmetry of the neonatal cerebral cortex. []. Published online October 13, 2021.
  SLCN
• Dimitrova R, Pietsch M, Ciarrusta J, et al.. Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age. NeuroImage. 2021;243:118488.
  SLCN
• Makropoulos A, Robinson EC, Schuh A, et al.. The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction. NeuroImage. 2018;173:88-112.
  SLCN
• Fawaz A, Williams LZJ, Alansary A, et al.. Benchmarking Geometric Deep Learning for Cortical Segmentation and Neurodevelopmental Phenotype Prediction. []. Published online December 2, 2021.
  SLCN
• Alves N, Schuurmans M, Litjens G, Bosma JS, Hermans J, Huisman H. Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography. Cancers. 2022;14(2):376.
  Pancreatic Ductal Adenocarcinoma Detection in CT
• Xie W, Jacobs C, Charbonnier J-P, van Ginneken B. Dense Regression Activation Maps For Lesion Segmentation in CT scans of COVID-19 patients. arXiv. Published online November 22, 2021.
• Liew S-L, Lo B, Donnelly MR, et al.. A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms. []. Published online December 11, 2021.
  ATLAS
• Tellez D, Litjens G, van der Laak J, Ciompi F. Neural Image Compression for Gigapixel Histopathology Image Analysis. IEEE Trans Pattern Anal Mach Intell. 2021;43(2):567-578.
  Neural Image Compression
• Xie W, Jacobs C, Charbonnier J-P, van Ginneken B. Structure and position-aware graph neural network for airway labeling. arXiv. Published online January 13, 2022.
  Airway Anatomical Labeling
• Xu F, Zhu C, Tang W, et al.. Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides. Front Oncol. 2021;11.
  BCNB
• He Y, Yang G, Yang J, et al.. Meta grayscale adaptive network for 3D integrated renal structures segmentation. Medical Image Analysis. 2021;71:102055.
  kipa22
• He Y, Yang G, Yang J, et al.. Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation. Medical Image Analysis. 2020;63:101722.
  kipa22
• Lin Z, Wei D, Petkova MD, et al.. NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale. Lecture Notes in Computer Science. Published online 2021:164-174.
  NucMM
• Xie W, Jacobs C, Charbonnier J-P, van Ginneken B. Relational Modeling for Robust and Efficient Pulmonary Lobe Segmentation in CT Scans. IEEE Trans Med Imaging. 2020;39(8):2664-2675.
  Pulmonary Lobe Segmentation
• Liao F, Liang M, Li Z, Hu X, Song S. Evaluate the Malignancy of Pulmonary Nodules Using the 3-D Deep Leaky Noisy-OR Network. IEEE Trans Neural Netw Learning Syst. 2019;30(11):3484-3495.
  Lung cancer risk estimation on thorax CT scans - DSB2017 grt123
• Jacobs C, Setio AAA, Scholten ET, et al.. Deep Learning for Lung Cancer Detection on Screening CT Scans: Results of a Large-Scale Public Competition and an Observer Study with 11 Radiologists. Radiology: Artificial Intelligence. 2021;3(6).
  Lung cancer risk estimation on thorax CT scans - DSB2017 grt123 Lung cancer risk estimation on thorax CT scans - DSB2017 JulianDaniel
• Graham S, Jahanifar M, Vu QD, et al.. CoNIC: Colon Nuclei Identification and Counting Challenge 2022. arXiv. Published online November 30, 2021.
  CoNIC-Challenge
• Cassidy B, Kendrick C, Reeves ND, et al.. Diabetic Foot Ulcer Grand Challenge 2021: Evaluation and Summary. Lecture Notes in Computer Science. Published online 2022:90-105.
  DFU-2021
• Wolterink JM, Leiner T, de Vos BD, van Hamersvelt RW, Viergever MA, Išgum I. Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks. Medical Image Analysis. 2016;34:123-136.
• Geijs DJ, Pinckaers H, Amir AL, Litjens GJS. End-to-end classification on basal-cell carcinoma histopathology whole-slides images. Tomaszewski JE, Ward AD, eds.. Medical Imaging 2021: Digital Pathology. Published online February 15, 2021:4.
• Meyer A, Rakr M, Schindele D, et al.. Towards Patient-Individual PI-Rads v2 Sector Map: Cnn for Automatic Segmentation of Prostatic Zones From T2-Weighted MRI. 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019). Published online April 2019:696-700.
• Saha A, Hosseinzadeh M, Huisman H. End-to-end prostate cancer detection in bpMRI via 3D CNNs: Effects of attention mechanisms, clinical priori and decoupled false positive reduction. Medical Image Analysis. 2021;73:102155.
  Clinically Significant Prostate Cancer Detection in bpMRI
• Hering A, Häger S, Moltz J, Lessmann N, Heldmann S, van Ginneken B. CNN-based lung CT registration with multiple anatomical constraints. Medical Image Analysis. 2021;72:102139.
  Deep-Learning-Based CT Lung Registration
• Mercan C, Balkenhol M, Salgado R, et al.. Automated Scoring of Nuclear Pleomorphism Spectrum with Pathologist-level Performance in Breast Cancer. arXiv. Published online December 25, 2020.
  Nuclear Pleomorphism Scoring
• Lessmann N, Wolterink JM, Zreik M, Viergever MA, van Ginneken B, Išgum I. Vertebra partitioning with thin-plate spline surfaces steered by a convolutional neural network. arXiv. Published online July 27, 2019.
• Cassidy B, Centre for Applied Computational Science, Faculty of Science and Engineering, Manchester Metropolitan University, Manchester, UK, Reeves ND, et al.. The DFUC 2020 Dataset: Analysis Towards Diabetic Foot Ulcer Detection. European Endocrinology. 2021;1(1):5.
  DFU2020
• Yap MH, Cassidy B, Pappachan JM, O'Shea C, Gillespie D, Reeves ND. Analysis Towards Classification of Infection and Ischaemia of Diabetic Foot Ulcers. 2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI). Published online July 27, 2021.
  DFU-2021
• Yap MH, Hachiuma R, Alavi A, et al.. Deep learning in diabetic foot ulcers detection: A comprehensive evaluation. Computers in Biology and Medicine. 2021;135:104596.
  DFU2020
• Aubreville M, Bertram C, Veta M, et al.. Quantifying the Scanner-Induced Domain Gap in Mitosis Detection. arXiv. Published online March 31, 2021.
  MIDOG2021
• Aubreville M, Bertram C, Veta M, et al.. MItosis DOmain Generalization Challenge. Published online March 2, 2021.
  MIDOG2021
• van Leeuwen KG, Schalekamp S, Rutten MJCM, van Ginneken B, de Rooij M. Artificial intelligence in radiology: 100 commercially available products and their scientific evidence. Eur Radiol. 2021;31(6):3797-3804.
• Verma R, Kumar N, Patil A, et al.. MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge. IEEE Trans Med Imaging. 2021;40(12):3413-3423.
  MoNuSAC-2020
• Petrick N, Akbar S, Cha KH, et al.. SPIE-AAPM-NCI BreastPathQ challenge: an image analysis challenge for quantitative tumor cellularity assessment in breast cancer histology images following neoadjuvant treatment. J Med Imag. 2021;8(03).
  BreastPathQ
• Hennemuth A, Goubergrits L, Ivantsits M, Kuhnigk J-M, eds.. Cerebral Aneurysm Detection. (Hennemuth A, Goubergrits L, Ivantsits M, Kuhnigk J-M, eds.). Springer International Publishing; 2021.
  CADA
• Venkadesh KV, Setio AAA, Schreuder A, et al.. Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT. Radiology. 2021;300(2):438-447.
  Pulmonary Nodule Malignancy Prediction
• Li J, Pimentel P, Szengel A, et al.. AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design. IEEE Trans Med Imaging. 2021;40(9):2329-2342.
  AutoImplant2021
• van Ginneken B, Jacobs C. LUNA16 Part 2/2. Published online March 17, 2019.
  LUNA16
• van Ginneken B, Jacobs C. LUNA16 Part 1/2. Published online March 16, 2019.
  LUNA16
• Ali S, Dmitrieva M, Ghatwary N, et al.. Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy. Medical Image Analysis. 2021;70:102002.
  EndoCV2022
• González‐Gonzalo C, Sánchez‐Gutiérrez V, Hernández‐Martínez P, et al.. Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age‐related macular degeneration. Acta Ophthalmologica. 2019;98(4):368-377.
• Kavur AE, Gezer NS, Barış M, et al.. CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation. Medical Image Analysis. 2021;69:101950.
  CHAOS
• Tellez D, Hoppener D, Verhoef C, et al.. Extending Unsupervised Neural Image Compression With Supervised Multitask Learning. arXiv. Published online April 16, 2020.
• Lessmann N, van Ginneken B, Zreik M, et al.. Automatic Calcium Scoring in Low-Dose Chest CT Using Deep Neural Networks With Dilated Convolutions. IEEE Trans Med Imaging. 2018;37(2):615-625.
• Borovec J, Kybic J, Arganda-Carreras I, et al.. ANHIR: Automatic Non-Rigid Histological Image Registration Challenge. IEEE Trans Med Imaging. 2020;39(10):3042-3052.
  ANHIR
• de Vente C, Boulogne LH, Venkadesh KV, et al.. Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study. arXiv. Published online September 22, 2020.
• Humpire-Mamani GE, Bukala J, Scholten ET, Prokop M, van Ginneken B, Jacobs C. Fully Automatic Volume Measurement of the Spleen at CT Using Deep Learning. Radiology: Artificial Intelligence. 2020;2(4):e190102.
• Irvin J, Rajpurkar P, Ko M, et al.. CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. arXiv. Published online January 23, 2019.
• Maier-Hein KH, Neher PF, Houde J-C, et al.. The challenge of mapping the human connectome based on diffusion tractography. Nat Commun. 2017;8(1).