Top Papers: KI in der Krebserkennung (2008)

Die 50 meistzitierten Arbeiten zu KI in der Krebserkennung aus dem Jahr 2008 (von 1.414 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.

2006 2007 2008 2009

#	Paper	Zitationen
1	How To Build and Interpret a Nomogram for Cancer Prognosis Alexia Iasonos, Deborah Schrag, Ganesh V. Raj et al. Journal of Clinical Oncology	3.347
2	Support vector machines combined with feature selection for breast cancer diagnosis Mehmet Fatih Akay Expert Systems with Applications	803
3	Object-Based Image Analysis Thomas Blaschke, Stefan Lang, Geoffrey J. Hay et al. Lecture notes in geoinformation and cartography	580
4	Four-Chamber Heart Modeling and Automatic Segmentation for 3-D Cardiac CT Volumes Using Marginal Space Learning and Steerable Features Yefeng Zheng, Adrian Barbu, Bogdan Georgescu et al. IEEE Transactions on Medical Imaging	550
5	Using Clinical Factors and Mammographic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model Jeffrey A. Tice, Steven R. Cummings, Rebecca Smith‐Bindman et al. Annals of Internal Medicine	539
6	Guideline implementation for breast healthcare in low-income and middle-income countries Benjamin O. Anderson, Cheng Har Yip, Robert A. Smith et al. Cancer	532
7	An expert system for detection of breast cancer based on association rules and neural network Murat Karabatak, M. Cevdet İnce Expert Systems with Applications	495
8	Exploring feature-based approaches in PET images for predicting cancer treatment outcomes Issam El Naqa, Perry W. Grigsby, Aditya Apte et al. Pattern Recognition	470
9	Diagnostic Accuracy of Digital versus Film Mammography: Exploratory Analysis of Selected Population Subgroups in DMIST Etta D. Pisano, R. Edward Hendrick, Martin J. Yaffe et al. Radiology	461
10	Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008 Dimitris Metaxas, Leon Axel, Gábor Fichtinger et al. Lecture notes in computer science	429
11	Mammographic density. Potential mechanisms of breast cancer risk associated with mammographic density: hypotheses based on epidemiological evidence Lisa J. Martin, Norman F. Boyd Breast Cancer Research	370
12	Breast tomosynthesis and digital mammography: a comparison of breast cancer visibility and BIRADS classification in a population of cancers with subtle mammographic findings Ingvar Andersson, Debra M. Ikeda, Sophia Zackrisson et al. European Radiology	341
13	Image Segmentation Based on 2D Otsu Method with Histogram Analysis Jun Zhang, Jinglu Hu —	327
14	Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology Shivang Naik, Scott Doyle, Shannon C. Agner et al. —	306
15	Anniversary Paper: History and status of CAD and quantitative image analysis: The role of<i>Medical Physics</i>and AAPM Maryellen L. Giger, Heang‐Ping Chan, John M. Boone Medical Physics	305
16	Receiver-operating characteristic curve analysis in diagnostic, prognostic and predictive biomarker research Kjetil Søreide Journal of Clinical Pathology	305
17	Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008 Valérie Duay, Xavier Bresson, Javier Castro et al. Lecture notes in computer science	289
18	Single Reading with Computer-Aided Detection for Screening Mammography Fiona J. Gilbert, Susan Astley, Maureen Gc Gillan et al. New England Journal of Medicine	289
19	Automated grading of breast cancer histopathology using spectral clusteringwith textural and architectural image features Scott Doyle, Shannon C. Agner, Anant Madabhushi et al. —	276
20	Sentinel Node Tumor Burden According to the Rotterdam Criteria Is the Most Important Prognostic Factor for Survival in Melanoma Patients Alexander C. J. van Akkooi, Zbigniew Nowecki, Christiane Voit et al. Annals of Surgery	253
21	Computing average shaped tissue probability templates John Ashburner, Karl Friston NeuroImage	238
22	Mammographic density. Measurement of mammographic density Martin J. Yaffe Breast Cancer Research	237
23	BodyParts3D: 3D structure database for anatomical concepts N Mitsuhashi, Kenji Fujieda, Takuro Tamura et al. Nucleic Acids Research	234
24	A Novel Breast Tissue Density Classification Methodology Arnau Oliver, Jordi Freixenet, Robert Martí et al. IEEE Transactions on Information Technology in Biomedicine	232
25	An improved Internet-based melanoma screening system with dermatologist-like tumor area extraction algorithm Hitoshi Iyatomi, Hiroshi Oka, M. Emre Celebi et al. Computerized Medical Imaging and Graphics	230
26	Quantitative Analysis of Lesion Morphology and Texture Features for Diagnostic Prediction in Breast MRI Ke Nie, Jeon‐Hor Chen, Hon J. Yu et al. Academic Radiology	228
27	A comparative study of survival models for breast cancer prognostication based on microarray data: does a single gene beat them all? Benjamin Haibe‐Kains, Christine Desmedt, Christos Sotiriou et al. Bioinformatics	220
28	Mammographic Images Enhancement and Denoising for Breast Cancer Detection Using Dyadic Wavelet Processing Arianna Mencattini, Marcello Salmeri, R. Lojacono et al. IEEE Transactions on Instrumentation and Measurement	216
29	Breast screening with ultrasound in women with mammography-negative dense breasts: Evidence on incremental cancer detection and false positives, and associated cost Vittorio Corsetti, Nehmat Houssami, Aurora Ferrari et al. European Journal of Cancer	214
30	Computer-aided prognosis of neuroblastoma on whole-slide images: Classification of stromal development Olcay Sertel, Jun Kong, Hiroyuki Shimada et al. Pattern Recognition	208
31	Brain Anatomical Structure Segmentation by Hybrid Discriminative/Generative Models Zhuowen Tu, Katherine L. Narr, Piotr Dollár et al. IEEE Transactions on Medical Imaging	189
32	Histopathological Image Analysis Using Model-Based Intermediate Representations and Color Texture: Follicular Lymphoma Grading Olcay Sertel, Jun Kong, Ümit V. Çatalyürek et al. Journal of Signal Processing Systems	189
33	Coregistered FDG PET/CT-Based Textural Characterization of Head and Neck Cancer for Radiation Treatment Planning Huan Yu, Curtis Caldwell, Kandice Mah et al. IEEE Transactions on Medical Imaging	188
34	Cost-Effectiveness of Digital Mammography Breast Cancer Screening Anna N.A. Tosteson, Natasha K. Stout, Dennis G. Fryback et al. Annals of Internal Medicine	186
35	The “Laboratory” Effect: Comparing Radiologists' Performance and Variability during Prospective Clinical and Laboratory Mammography Interpretations David Gur, Andriy I. Bandos, Cathy S. Cohen et al. Radiology	186
36	Breast Imaging Reporting and Data System (BI-RADS); Albert L. Baert —	180
37	A new fully automatic and robust algorithm for fast segmentation of liver tissue and tumors from CT scans Laurent Massoptier, Sergio Casciaro European Radiology	175
38	Development of a quantitative method for analysis of breast density based on three‐dimensional breast MRI Ke Nie, Jeon‐Hor Chen, Si‐Wa Chan et al. Medical Physics	170
39	3D Segmentation in the Clinic: A Grand Challenge II: MS lesion segmentation Martin Styner, Joohwi Lee, Brian Chin et al. —	169
40	An artificial multilayer perceptron neural network for diagnosis of proximal dental caries Karina Lopes Devito, Flávio de Souza Barbosa, Waldir Neme Felippe Filho Oral Surgery Oral Medicine Oral Pathology Oral Radiology and Endodontology	166
41	Fuzzy Local Binary Patterns for Ultrasound Texture Characterization Dimitris K. Iakovidis, Eystratios G. Keramidas, Dimitris Maroulis Lecture notes in computer science	165
42	ROC analysis with multiple classes and multiple tests: methodology and its application in microarray studies Jialiang Li, Jason P. Fine Biostatistics	163
43	Basic Physics and Doubts about Relationship between Mammographically Determined Tissue Density and Breast Cancer Risk Daniel B. Kopans Radiology	162
44	Segmentation and classification of medical images using texture-primitive features: Application of BAM-type artificial neural network Neeraj Sharma, AmitK Ray, Shiru Sharma et al. Journal of Medical Physics	161
45	Computer-aided evaluation of neuroblastoma on whole-slide histology images: Classifying grade of neuroblastic differentiation Jun Kong, Olcay Sertel, Hiroyuki Shimada et al. Pattern Recognition	160
46	Computer aids and human second reading as interventions in screening mammography: Two systematic reviews to compare effects on cancer detection and recall rate Paul Taylor, Henry Potts European Journal of Cancer	159
47	US-guided 14-gauge Core-Needle Breast Biopsy: Results of a Validation Study in 1352 Cases Gerd Schueller, Sylvia Jaromi, Lothar Ponhold et al. Radiology	157
48	The Bethesda System for Reporting Cervical Cytology Ritu Nayar, David C. Wilbur, Diane Solomon Elsevier eBooks	155
49	Digital Breast Tomosynthesis: A Pilot Observer Study Walter F. Good, Gordon S. Abrams, Victor J. Catullo et al. American Journal of Roentgenology	152
50	Using Gaze-tracking Data and Mixture Distribution Analysis to Support a Holistic Model for the Detection of Cancers on Mammograms Harold L. Kundel, Calvin F. Nodine, Elizabeth A. Krupinski et al. Academic Radiology	151

Top Papers: KI in der Krebserkennung (2008)

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