359 related articles for article (PubMed ID: 27528421)
1. Computer-aided diagnosis of breast cancer using cytological images: A systematic review.
Saha M; Mukherjee R; Chakraborty C
Tissue Cell; 2016 Oct; 48(5):461-74. PubMed ID: 27528421
[TBL] [Abstract][Full Text] [Related]
2. Computer-aided diagnosis of breast cancer based on fine needle biopsy microscopic images.
Kowal M; Filipczuk P; Obuchowicz A; Korbicz J; Monczak R
Comput Biol Med; 2013 Oct; 43(10):1563-72. PubMed ID: 24034748
[TBL] [Abstract][Full Text] [Related]
3. [Needle aspiration cytology of the breast: current perspective on the role in diagnosis and management].
Kocjan G
Acta Med Croatica; 2008 Oct; 62(4):391-401. PubMed ID: 19205416
[TBL] [Abstract][Full Text] [Related]
4. Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review.
Yassin NIR; Omran S; El Houby EMF; Allam H
Comput Methods Programs Biomed; 2018 Mar; 156():25-45. PubMed ID: 29428074
[TBL] [Abstract][Full Text] [Related]
5. Influence of feature set reduction on breast cancer malignancy classification of fine needle aspiration biopsies.
Jeleń Ł; Krzyżak A; Fevens T; Jeleń M
Comput Biol Med; 2016 Dec; 79():80-91. PubMed ID: 27768905
[TBL] [Abstract][Full Text] [Related]
6. Multi-label fast marching and seeded watershed segmentation methods for diagnosis of breast cancer cytology.
Filipczuk P; Kowal M; Obuchowicz A
Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():7368-71. PubMed ID: 24111447
[TBL] [Abstract][Full Text] [Related]
7. Computer-aided diagnosis of contrast-enhanced spectral mammography: A feasibility study.
Patel BK; Ranjbar S; Wu T; Pockaj BA; Li J; Zhang N; Lobbes M; Zhang B; Mitchell JR
Eur J Radiol; 2018 Jan; 98():207-213. PubMed ID: 29279165
[TBL] [Abstract][Full Text] [Related]
8. [Computer-aided Prognosis for Breast Cancer Based on Hematoxylin & Eosin Histopathology Image].
Chen J; Qu A; Liu W; Wang L; Yuan J; Liu J; Li Y
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2016 Jun; 33(3):598-603. PubMed ID: 29709166
[TBL] [Abstract][Full Text] [Related]
9. Imprint cytology-based breast malignancy screening: an efficient nuclei segmentation technique.
Saha M; Arun I; Agarwal S; Ahmed R; Chatterjee S; Chakraborty C
J Microsc; 2017 Nov; 268(2):155-171. PubMed ID: 28654222
[TBL] [Abstract][Full Text] [Related]
10. Convolutional neural networks for computer-aided detection or diagnosis in medical image analysis: An overview.
Gao J; Jiang Q; Zhou B; Chen D
Math Biosci Eng; 2019 Jul; 16(6):6536-6561. PubMed ID: 31698575
[TBL] [Abstract][Full Text] [Related]
11. Towards high performance cell segmentation in multispectral fine needle aspiration cytology of thyroid lesions.
Gabriel E; Venkatesan V; Shah S
Comput Methods Programs Biomed; 2010 Jun; 98(3):231-40. PubMed ID: 19720425
[TBL] [Abstract][Full Text] [Related]
12. Imprint cytology from core biopsies increases the sensitivity of fine needle aspiration (FNA) in breast cancer patients.
Dayal S; Murray J; Wilson K; Lannigan A
Magy Seb; 2011 Apr; 64(2):59-62. PubMed ID: 21504853
[TBL] [Abstract][Full Text] [Related]
13. Fine needle aspiration cytology of lymph nodes in breast cancer follow-up is a feasible alternative to watchful waiting and to histology.
Hammon M; Dankerl P; Janka R; Wachter DL; Hartmann A; Schulz-Wendtland R; Uder M; Wenkel E
BMC Womens Health; 2015 Dec; 15():114. PubMed ID: 26631071
[TBL] [Abstract][Full Text] [Related]
14. Evaluation of fine needle aspiration and imprint cytology in the early diagnosis of breast lesions with histopathological correlation.
Dutta SK; Chattopadhyaya A; Roy S
J Indian Med Assoc; 2001 Aug; 99(8):421-3. PubMed ID: 11881855
[TBL] [Abstract][Full Text] [Related]
15. Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.
Giger ML; Chan HP; Boone J
Med Phys; 2008 Dec; 35(12):5799-820. PubMed ID: 19175137
[TBL] [Abstract][Full Text] [Related]
16. A computer-aided diagnosis system for dynamic contrast-enhanced MR images based on level set segmentation and ReliefF feature selection.
Pang Z; Zhu D; Chen D; Li L; Shao Y
Comput Math Methods Med; 2015; 2015():450531. PubMed ID: 25628755
[TBL] [Abstract][Full Text] [Related]
17. Pitfalls in diagnosing specific subtypes of carcinoma breast on fine needle aspiration cytology: a report of two cases with review of literature.
Anantharamaiah H; Raju K; Suresh SP; Manikyam UK
J Cancer Res Ther; 2012; 8(3):454-6. PubMed ID: 23174736
[TBL] [Abstract][Full Text] [Related]
18. Comparative Study of Core Needle Biopsy and Fine Needle Aspiration Cytology in Palpable Breast Lumps: Scenario in Developing Nations.
Tikku G; Umap P
Turk Patoloji Derg; 2016; 32(1):1-7. PubMed ID: 26832175
[TBL] [Abstract][Full Text] [Related]
19. Breast fine-needle aspiration cytology performance in the high-risk screening population: a study of BRCA1/BRCA2 mutation carriers.
Georgieva RD; Obdeijn IM; Jager A; Hooning MJ; Tilanus-Linthorst MM; van Deurzen CH
Cancer Cytopathol; 2013 Oct; 121(10):561-7. PubMed ID: 23720450
[TBL] [Abstract][Full Text] [Related]
20. Comparative assessment of CNN architectures for classification of breast FNAC images.
Saikia AR; Bora K; Mahanta LB; Das AK
Tissue Cell; 2019 Apr; 57():8-14. PubMed ID: 30947968
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
