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Alle Papers – KI in der Krebserkennung

168.310 Papers insgesamt · Seite 10 von 400

226.

Breast Cancer Histopathology Image Analysis: A Review

2014·692 Zit.·IEEE Transactions on Biomedical Engineering
227.

Machine learning and radiology

2012·683 Zit.·Medical Image AnalysisOA
228.

Improved Automatic Detection and Segmentation of Cell Nuclei in Histopathology Images

2009·681 Zit.·IEEE Transactions on Biomedical Engineering
229.

Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net)\n for Medical Image Segmentation

2018·681 Zit.·arXiv (Cornell University)OA
230.

Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks With Jaccard Distance

2017·680 Zit.·IEEE Transactions on Medical Imaging
231.

Multi-atlas segmentation of biomedical images: A survey

2015·677 Zit.·Medical Image Analysis
232.

Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond

2021·677 Zit.·Information FusionOA
233.

AI applications to medical images: From machine learning to deep learning

2021·677 Zit.·Physica MedicaOA
234.

The Influence of Margin Width on Local Control of Ductal Carcinoma in Situ of the Breast

1999·674 Zit.·New England Journal of MedicineOA
235.

Segmentation of Nuclei in Histopathology Images by Deep Regression of the Distance Map

2018·673 Zit.·IEEE Transactions on Medical Imaging
236.

Computed Tomographic Colonography (Virtual Colonoscopy)

2004·672 Zit.·JAMA
237.

Attention-based Deep Multiple Instance Learning

2018·671 Zit.·arXiv (Cornell University)OA
238.

Multimodal deep learning models for early detection of Alzheimer’s disease stage

2021·670 Zit.·Scientific ReportsOA
239.

A methodological approach to the classification of dermoscopy images

2007·669 Zit.·Computerized Medical Imaging and Graphics
240.

Diagnostic Accuracy of Digital Screening Mammography With and Without Computer-Aided Detection

2015·668 Zit.·JAMA Internal MedicineOA
241.

Data augmentation using generative adversarial networks (CycleGAN) to improve generalizability in CT segmentation tasks

2019·668 Zit.·Scientific ReportsOA
242.

Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model

2017·667 Zit.·Scientific ReportsOA
243.

Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study

2020·662 Zit.·The Lancet OncologyOA
244.

Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis

2020·659 Zit.·Nature Cancer
245.

Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists

2018·655 Zit.·JNCI Journal of the National Cancer InstituteOA
246.

Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening

2019·655 Zit.·IEEE Transactions on Medical ImagingOA
247.

BACH: Grand challenge on breast cancer histology images

2019·654 Zit.·Medical Image AnalysisOA
248.

The Potential of Radiomic-Based Phenotyping in Precision Medicine

2016·652 Zit.·JAMA Oncology
249.

A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT

2020·650 Zit.·IEEE Transactions on Medical Imaging
250.

National Performance Benchmarks for Modern Screening Digital Mammography: Update from the Breast Cancer Surveillance Consortium

2016·650 Zit.·RadiologyOA