Top Papers: KI in der Krebserkennung (2013)

Die 50 meistzitierten Arbeiten zu KI in der Krebserkennung aus dem Jahr 2013 (von 2.084 insgesamt).

Krebs frühzeitig zu erkennen kann Leben retten – und genau hier setzt KI an. Deep-Learning-Modelle erreichen inzwischen bei bestimmten Tumorarten eine Erkennungsgenauigkeit, die mit der erfahrener Pathologen vergleichbar ist. Die Forschung umfasst Hautkrebs-Screening, Brustkrebs-Mammographie, Lungennoduli-Erkennung und vieles mehr. Hier finden Sie die einflussreichsten und neuesten Studien zu diesem Thema.

2011 2012 2013 2014

#	Paper	Zitationen
1	Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks Dan Cireşan, Alessandro Giusti, Luca Maria Gambardella et al. Lecture notes in computer science	1.545
2	Comparison of Digital Mammography Alone and Digital Mammography Plus Tomosynthesis in a Population-based Screening Program Per Skaane, Andriy I. Bandos, Randi Gullien et al. Radiology	996
3	Quantitative Analysis of Histological Staining and Fluorescence Using ImageJ Ellen C. Jensen The Anatomical Record	943
4	PH<sup>2</sup> - A dermoscopic image database for research and benchmarking Teresa Mendonça, Pedro M. Ferreira, Jorge S. Marques et al. —	917
5	Principles for Valid Histopathologic Scoring in Research Katherine N. Gibson‐Corley, Alicia K. Olivier, David K. Meyerholz Veterinary Pathology	845
6	Integration of 3D digital mammography with tomosynthesis for population breast-cancer screening (STORM): a prospective comparison study Stefano Ciatto, Nehmat Houssami, Daniela Bernardi et al. The Lancet Oncology	826
7	Validating Whole Slide Imaging for Diagnostic Purposes in Pathology: Guideline from the College of American Pathologists Pathology and Laboratory Quality Center Liron Pantanowitz, John H. Sinard, Walter H. Henricks et al. Archives of Pathology & Laboratory Medicine	593
8	OpenSlide: A vendor-neutral software foundation for digital pathology Adam Goode, Ben Gilbert, Jan Harkes et al. Journal of Pathology Informatics	556
9	Breast cancer diagnosis based on feature extraction using a hybrid of K-means and support vector machine algorithms Bichen Zheng, Sang Won Yoon, Sarah S. Lam Expert Systems with Applications	546
10	Comparison of Tomosynthesis Plus Digital Mammography and Digital Mammography Alone for Breast Cancer Screening Brian M. Haas, Vivek B. Kalra, Jaime Geisel et al. Radiology	413
11	A Deep Learning Architecture for Image Representation, Visual Interpretability and Automated Basal-Cell Carcinoma Cancer Detection Ángel Cruz-Roa, John Arévalo, Anant Madabhushi et al. Lecture notes in computer science	397
12	Diagnostic Inaccuracy of Smartphone Applications for Melanoma Detection Joel Wolf, Jacqueline F. Moreau, Oleg E. Akilov et al. JAMA Dermatology	393
13	OpenCFU, a New Free and Open-Source Software to Count Cell Colonies and Other Circular Objects Quentin Geissmann PLoS ONE	387
14	Automatic Nuclei Segmentation in H&E Stained Breast Cancer Histopathology Images Mitko Veta, P. J. van Diest, Robert Kornegoor et al. PLoS ONE	363
15	Lung cancer classification using neural networks for CT images Jinsa Kuruvilla, K. Gunavathi Computer Methods and Programs in Biomedicine	360
16	ACR Appropriateness Criteria Breast Cancer Screening Martha B. Mainiero, Ana P. Lourenço, Mary C. Mahoney et al. Journal of the American College of Radiology	341
17	Computer Aided Diagnostic Support System for Skin Cancer: A Review of Techniques and Algorithms Ammara Masood, Adel Al-Jumaily International Journal of Biomedical Imaging	336
18	A New Database for Breast Research with Infrared Image L. F. Silva, Débora Christina Muchaluat Saade, Giomar Oliver Sequeiros et al. Journal of Medical Imaging and Health Informatics	332
19	Implementation of Breast Tomosynthesis in a Routine Screening Practice: An Observational Study Stephen L. Rose, Andra L. Tidwell, Louis J. Bujnoch et al. American Journal of Roentgenology	327
20	Breast Ultrasonography: State of the Art Regina J. Hooley, Leslie M. Scoutt, Liane E. Philpotts Radiology	319
21	CT texture analysis using the filtration-histogram method: what do the measurements mean? Kenneth A. Miles, Balaji Ganeshan, Michael P. Hayball Cancer Imaging	311
22	The Virtual Skeleton Database: An Open Access Repository for Biomedical Research and Collaboration Michael Kistler, Serena Bonaretti, Marcel Pfahrer et al. Journal of Medical Internet Research	308
23	Random forest classifier combined with feature selection for breast cancer diagnosis and prognostic Cuong Tuan Nguyen, Yong Wang, Ha Nam Nguyen Journal of Biomedical Science and Engineering	308
24	Mitosis detection in breast cancer histological images An ICPR 2012 contest Roux Ludovic, Daniel Racoceanu, Nicolas Loménie et al. Journal of Pathology Informatics	302
25	Computer-Aided Diagnosis Systems for Lung Cancer: Challenges and Methodologies Ayman El‐Baz, Garth M. Beache, Georgy Gimel’farb et al. International Journal of Biomedical Imaging	276
26	A High-Resolution Enhancer Atlas of the Developing Telencephalon Axel Visel, Leila Taher, Hani Z. Girgis et al. Cell	276
27	Computer-aided diagnosis of breast cancer based on fine needle biopsy microscopic images Marek Kowal, Paweł Filipczuk, Andrzej Obuchowicz et al. Computers in Biology and Medicine	272
28	Using Three Machine Learning Techniques for Predicting Breast Cancer Recurrence Ahmad LG, Eshlaghy AT Journal of Health & Medical Informatics	270
29	Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images Colin Jacobs, Eva M. van Rikxoort, Thorsten Twellmann et al. Medical Image Analysis	259
30	Pathology imaging informatics for quantitative analysis of whole-slide images Sonal Kothari, John H. Phan, Todd H. Stokes et al. Journal of the American Medical Informatics Association	255
31	Three-dimensional solid texture analysis in biomedical imaging: Review and opportunities Adrien Depeursinge, Antonio Foncubierta–Rodríguez, Dimitri Van De Ville et al. Medical Image Analysis	246
32	An ensemble classifier system for early diagnosis of acute lymphoblastic leukemia in blood microscopic images Subrajeet Mohapatra, Dipti Patra, Sanghamitra Satpathy Neural Computing and Applications	243
33	IS&T/SPIE Electronic Imaging SPIE SPIE Professional	240
34	Content-Based Medical Image Retrieval: A Survey of Applications to Multidimensional and Multimodality Data Ashnil Kumar, Jinman Kim, Weidong Cai et al. Journal of Digital Imaging	230
35	If You Don’t Find It Often, You Often Don’t Find It: Why Some Cancers Are Missed in Breast Cancer Screening Karla K. Evans, Robyn L. Birdwell, Jeremy M. Wolfe PLoS ONE	229
36	Computer-Aided Breast Cancer Diagnosis Based on the Analysis of Cytological Images of Fine Needle Biopsies Paweł Filipczuk, Thomas Fevens, Adam Krzyżak et al. IEEE Transactions on Medical Imaging	228
37	Manifold Learning of Brain MRIs by Deep Learning Tom Brosch, Roger Tam, Roger Tam Lecture notes in computer science	225
38	Beyond Mammography: New Frontiers in Breast Cancer Screening Jennifer S. Drukteinis, Blaise Mooney, Chris I. Flowers et al. The American Journal of Medicine	223
39	Prospective trial comparing full-field digital mammography (FFDM) versus combined FFDM and tomosynthesis in a population-based screening programme using independent double reading with arbitration Per Skaane, Andriy I. Bandos, Randi Gullien et al. European Radiology	220
40	Breast Image Analysis for Risk Assessment, Detection, Diagnosis, and Treatment of Cancer Maryellen L. Giger, Nico Karssemeijer, Julia A. Schnabel Annual Review of Biomedical Engineering	208
41	Cancer Digital Slide Archive: an informatics resource to support integrated in silico analysis of TCGA pathology data David A. Gutman, Jake Cobb, Dhananjaya Somanna et al. Journal of the American Medical Informatics Association	203
42	Characterization of cell lines derived from breast cancers and normal mammary tissues for the study of the intrinsic molecular subtypes Aleix Prat, Olga Karginova, Joel S. Parker et al. Breast Cancer Research and Treatment	201
43	Remote Computer-Aided Breast Cancer Detection and Diagnosis System Based on Cytological Images Yasmeen George, Hala H. Zayed, Mohamed Roushdy et al. IEEE Systems Journal	200
44	Classification of mitotic figures with convolutional neural networks and seeded blob features Christopher D. Malon, Eric Cosatto Journal of Pathology Informatics	198
45	Large Sample Size, Wide Variant Spectrum, and Advanced Machine-Learning Technique Boost Risk Prediction for Inflammatory Bowel Disease Zhi Wei, Wei Wang, Jonathan P. Bradfield et al. The American Journal of Human Genetics	198
46	Quick‐and‐clean article figures with FigureJ Jérôme Mutterer, E. ZINCK Journal of Microscopy	187
47	Mass Classification in Mammograms Using Selected Geometry and Texture Features, and a New SVM-Based Feature Selection Method Xiaoming Liu, Jinshan Tang IEEE Systems Journal	185
48	Mammographic density and risk of breast cancer by age and tumor characteristics Kimberly A. Bertrand, Rulla M. Tamimi, Christopher G. Scott et al. Breast Cancer Research	184
49	A high quality finger vascular pattern dataset collected using a custom designed capturing device Bram Ton, Raymond Veldhuis —	182
50	Going fully digital: Perspective of a Dutch academic pathology lab Nikolas Stathonikos, Mitko Veta, André Huisman et al. Journal of Pathology Informatics	164

Top Papers: KI in der Krebserkennung (2013)

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