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Alle Papers – KI in der Krebserkennung

168.310 Papers insgesamt · Seite 40 von 400

976.

Deep learning-based transformation of H&E stained tissues into special stains

2021·281 Zit.·Nature CommunicationsOA
977.

Partial volume tissue classification of multichannel magnetic resonance images-a mixel model

1991·281 Zit.·IEEE Transactions on Medical Imaging
978.

The value of latent class analysis in medical diagnosis

1986·281 Zit.·Statistics in Medicine
979.

Mammographic densities and risk of breast cancer

1991·280 Zit.·CancerOA
980.

Deep learning in medical image analysis: A third eye for doctors

2019·280 Zit.·Journal of Stomatology Oral and Maxillofacial SurgeryOA
981.

Cross-level Feature Aggregation Network for Polyp Segmentation

2023·280 Zit.·Pattern Recognition
982.

Identifying Women With Dense Breasts at High Risk for Interval Cancer

2015·280 Zit.·Annals of Internal Medicine
983.

A Review of Deep Learning on Medical Image Analysis

2020·280 Zit.·Mobile Networks and Applications
984.

Stereotaxic 14-gauge breast biopsy: how many core biopsy specimens are needed?

1994·280 Zit.·Radiology
985.

Influence of gray level discretization on radiomic feature stability for different CT scanners, tube currents and slice thicknesses: a comprehensive phantom study

2017·280 Zit.·Acta OncologicaOA
986.

Skin Lesion Classification Using Convolutional Neural Network With Novel Regularizer

2019·279 Zit.·IEEE AccessOA
987.

Mammographic parenchymal patterns and quantitative evaluation of mammographic densities: a case-control study

1987·279 Zit.·American Journal of Roentgenology
988.

Literature review: efficient deep neural networks techniques for medical image analysis

2022·279 Zit.·Neural Computing and Applications
989.

Deep learning-based multi-view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre study

2020·279 Zit.·European Journal of RadiologyOA
990.

Brain Imaging Generation with Latent Diffusion Models

2022·279 Zit.·Lecture notes in computer science
991.

Large-scale pancreatic cancer detection via non-contrast CT and deep learning

2023·279 Zit.·Nature MedicineOA
992.

A survey on U-shaped networks in medical image segmentations

2020·279 Zit.·Neurocomputing
993.

Gradient and texture analysis for the classification of mammographic masses

2000·279 Zit.·IEEE Transactions on Medical Imaging
994.

Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study

2020·279 Zit.·The Lancet Digital HealthOA
995.

Computer-aided mammographic screening for spiculated lesions.

1994·278 Zit.·Radiology
996.

Deep Learning Algorithms for Detection of Lymph Node Metastases From Breast Cancer

2017·278 Zit.·JAMA
997.

A deep transfer learning model with classical data augmentation and CGAN to detect COVID-19 from chest CT radiography digital images

2020·278 Zit.·Neural Computing and ApplicationsOA
998.

Computer-Aided Diagnosis Systems for Lung Cancer: Challenges and Methodologies

2013·277 Zit.·International Journal of Biomedical ImagingOA
999.

Breast cancer screening with tomosynthesis (3D mammography) with acquired or synthetic 2D mammography compared with 2D mammography alone (STORM-2): a population-based prospective study

2016·277 Zit.·The Lancet Oncology
1000.

Computed Tomographic Virtual Colonoscopy Computer-Aided Polyp Detection in a Screening Population

2005·277 Zit.·GastroenterologyOA