273 related articles for article (PubMed ID: 29185058)
1. Content-based image retrieval for Lung Nodule Classification Using Texture Features and Learned Distance Metric.
Wei G; Cao H; Ma H; Qi S; Qian W; Ma Z
J Med Syst; 2017 Nov; 42(1):13. PubMed ID: 29185058
[TBL] [Abstract][Full Text] [Related]
2. Content-based retrieval for lung nodule diagnosis using learned distance metric.
Guohui Wei ; He Ma ; Wei Qian ; Hongyang Jiang ; Xinzhuo Zhao
Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():3910-3913. PubMed ID: 29060752
[TBL] [Abstract][Full Text] [Related]
3. Content-Based Image Retrieval System for Pulmonary Nodules: Assisting Radiologists in Self-Learning and Diagnosis of Lung Cancer.
Dhara AK; Mukhopadhyay S; Dutta A; Garg M; Khandelwal N
J Digit Imaging; 2017 Feb; 30(1):63-77. PubMed ID: 27678255
[TBL] [Abstract][Full Text] [Related]
4. Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: localized search method based on anatomical classification.
Shiraishi J; Li Q; Suzuki K; Engelmann R; Doi K
Med Phys; 2006 Jul; 33(7):2642-53. PubMed ID: 16898468
[TBL] [Abstract][Full Text] [Related]
5. Rapid Retrieval of Lung Nodule CT Images Based on Hashing and Pruning Methods.
Pan L; Qiang Y; Yuan J; Wu L
Biomed Res Int; 2016; 2016():3162649. PubMed ID: 27995140
[TBL] [Abstract][Full Text] [Related]
6. A weighted rule based method for predicting malignancy of pulmonary nodules by nodule characteristics.
Kaya A; Can AB
J Biomed Inform; 2015 Aug; 56():69-79. PubMed ID: 26008877
[TBL] [Abstract][Full Text] [Related]
7. Automatic weighing attribute to retrieve similar lung cancer nodules.
Ferreira de Lucena DJ; Ferreira Junior JR; Machado AP; Oliveira MC
BMC Med Inform Decis Mak; 2016 Jul; 16 Suppl 2(Suppl 2):79. PubMed ID: 27460071
[TBL] [Abstract][Full Text] [Related]
8. Assessment of performance and reproducibility of applying a content-based image retrieval scheme for classification of breast lesions.
Gundreddy RR; Tan M; Qiu Y; Cheng S; Liu H; Zheng B
Med Phys; 2015 Jul; 42(7):4241-9. PubMed ID: 26133622
[TBL] [Abstract][Full Text] [Related]
9. Content-Based Image Retrieval System for Pulmonary Nodules Using Optimal Feature Sets and Class Membership-Based Retrieval.
Mehre SA; Dhara AK; Garg M; Kalra N; Khandelwal N; Mukhopadhyay S
J Digit Imaging; 2019 Jun; 32(3):362-385. PubMed ID: 30361935
[TBL] [Abstract][Full Text] [Related]
10. A new computationally efficient CAD system for pulmonary nodule detection in CT imagery.
Messay T; Hardie RC; Rogers SK
Med Image Anal; 2010 Jun; 14(3):390-406. PubMed ID: 20346728
[TBL] [Abstract][Full Text] [Related]
11. Computer-aided lung nodule recognition by SVM classifier based on combination of random undersampling and SMOTE.
Sui Y; Wei Y; Zhao D
Comput Math Methods Med; 2015; 2015():368674. PubMed ID: 25977704
[TBL] [Abstract][Full Text] [Related]
12. Computer-aided diagnosis of pulmonary nodules on CT scans: segmentation and classification using 3D active contours.
Way TW; Hadjiiski LM; Sahiner B; Chan HP; Cascade PN; Kazerooni EA; Bogot N; Zhou C
Med Phys; 2006 Jul; 33(7):2323-37. PubMed ID: 16898434
[TBL] [Abstract][Full Text] [Related]
13. Shape and texture based novel features for automated juxtapleural nodule detection in lung CTs.
Taşcı E; Uğur A
J Med Syst; 2015 May; 39(5):46. PubMed ID: 25732079
[TBL] [Abstract][Full Text] [Related]
14. A novel computer-aided lung nodule detection system for CT images.
Tan M; Deklerck R; Jansen B; Bister M; Cornelis J
Med Phys; 2011 Oct; 38(10):5630-45. PubMed ID: 21992380
[TBL] [Abstract][Full Text] [Related]
15. Segmentation of pulmonary nodules in computed tomography using a regression neural network approach and its application to the Lung Image Database Consortium and Image Database Resource Initiative dataset.
Messay T; Hardie RC; Tuinstra TR
Med Image Anal; 2015 May; 22(1):48-62. PubMed ID: 25791434
[TBL] [Abstract][Full Text] [Related]
16. Computer-aided diagnosis of pulmonary nodules on CT scans: improvement of classification performance with nodule surface features.
Way TW; Sahiner B; Chan HP; Hadjiiski L; Cascade PN; Chughtai A; Bogot N; Kazerooni E
Med Phys; 2009 Jul; 36(7):3086-98. PubMed ID: 19673208
[TBL] [Abstract][Full Text] [Related]
17. Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network.
Suzuki K; Li F; Sone S; Doi K
IEEE Trans Med Imaging; 2005 Sep; 24(9):1138-50. PubMed ID: 16156352
[TBL] [Abstract][Full Text] [Related]
18. A joint ROI extraction filter for computer aided lung nodule detection.
Shi Z; Xu B; Zhao M; Zhao J; Wang Y; Liu Y; Zhang M; He L; Suzuki K
Biomed Mater Eng; 2015; 26 Suppl 1():S1491-9. PubMed ID: 26405913
[TBL] [Abstract][Full Text] [Related]
19. A Segmentation Framework of Pulmonary Nodules in Lung CT Images.
Mukhopadhyay S
J Digit Imaging; 2016 Feb; 29(1):86-103. PubMed ID: 26055544
[TBL] [Abstract][Full Text] [Related]
20. An automated CT based lung nodule detection scheme using geometric analysis of signed distance field.
Pu J; Zheng B; Leader JK; Wang XH; Gur D
Med Phys; 2008 Aug; 35(8):3453-61. PubMed ID: 18777905
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]