302 related articles for article (PubMed ID: 33973065)
1. Augmenting Transfer Learning with Feature Extraction Techniques for Limited Breast Imaging Datasets.
R V A; R A; A P S
J Digit Imaging; 2021 Jun; 34(3):618-629. PubMed ID: 33973065
[TBL] [Abstract][Full Text] [Related]
2. Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography.
Mendel K; Li H; Sheth D; Giger M
Acad Radiol; 2019 Jun; 26(6):735-743. PubMed ID: 30076083
[TBL] [Abstract][Full Text] [Related]
3. Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography.
Samala RK; Chan HP; Hadjiiski L; Helvie MA; Wei J; Cha K
Med Phys; 2016 Dec; 43(12):6654. PubMed ID: 27908154
[TBL] [Abstract][Full Text] [Related]
4. A Multilevel Transfer Learning Technique and LSTM Framework for Generating Medical Captions for Limited CT and DBT Images.
Aswiga RV; Shanthi AP
J Digit Imaging; 2022 Jun; 35(3):564-580. PubMed ID: 35217942
[TBL] [Abstract][Full Text] [Related]
5. A deep learning classifier for digital breast tomosynthesis.
Ricciardi R; Mettivier G; Staffa M; Sarno A; Acampora G; Minelli S; Santoro A; Antignani E; Orientale A; Pilotti IAM; Santangelo V; D'Andria P; Russo P
Phys Med; 2021 Mar; 83():184-193. PubMed ID: 33798904
[TBL] [Abstract][Full Text] [Related]
6. Characterization of masses in digital breast tomosynthesis: comparison of machine learning in projection views and reconstructed slices.
Chan HP; Wu YT; Sahiner B; Wei J; Helvie MA; Zhang Y; Moore RH; Kopans DB; Hadjiiski L; Way T
Med Phys; 2010 Jul; 37(7):3576-86. PubMed ID: 20831065
[TBL] [Abstract][Full Text] [Related]
7. Breast Cancer Diagnosis in Digital Breast Tomosynthesis: Effects of Training Sample Size on Multi-Stage Transfer Learning Using Deep Neural Nets.
Samala RK; Heang-Ping Chan ; Hadjiiski L; Helvie MA; Richter CD; Cha KH
IEEE Trans Med Imaging; 2019 Mar; 38(3):686-696. PubMed ID: 31622238
[TBL] [Abstract][Full Text] [Related]
8. Digital breast tomosynthesis versus digital mammography: integration of image modalities enhances deep learning-based breast mass classification.
Li X; Qin G; He Q; Sun L; Zeng H; He Z; Chen W; Zhen X; Zhou L
Eur Radiol; 2020 Feb; 30(2):778-788. PubMed ID: 31691121
[TBL] [Abstract][Full Text] [Related]
9. Architectural distortion detection based on superior-inferior directional context and anatomic prior knowledge in digital breast tomosynthesis.
Li Y; He Z; Ma X; Zeng W; Liu J; Xu W; Xu Z; Wang S; Wen C; Zeng H; Wu J; Chen W; Lu Y
Med Phys; 2022 Jun; 49(6):3749-3768. PubMed ID: 35338787
[TBL] [Abstract][Full Text] [Related]
10. Image feature evaluation in two new mammography CAD prototypes.
Hapfelmeier A; Horsch A
Int J Comput Assist Radiol Surg; 2011 Nov; 6(6):721-35. PubMed ID: 21380554
[TBL] [Abstract][Full Text] [Related]
11. Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network.
Kooi T; van Ginneken B; Karssemeijer N; den Heeten A
Med Phys; 2017 Mar; 44(3):1017-1027. PubMed ID: 28094850
[TBL] [Abstract][Full Text] [Related]
12. Digital breast tomosynthesis and contrast-enhanced dual-energy digital mammography alone and in combination compared to 2D digital synthetized mammography and MR imaging in breast cancer detection and classification.
Petrillo A; Fusco R; Vallone P; Filice S; Granata V; Petrosino T; Rosaria Rubulotta M; Setola SV; Mattace Raso M; Maio F; Raiano C; Siani C; Di Bonito M; Botti G
Breast J; 2020 May; 26(5):860-872. PubMed ID: 31886607
[TBL] [Abstract][Full Text] [Related]
13. Mass detection in digital breast tomosynthesis data using convolutional neural networks and multiple instance learning.
Yousefi M; Krzyżak A; Suen CY
Comput Biol Med; 2018 May; 96():283-293. PubMed ID: 29665537
[TBL] [Abstract][Full Text] [Related]
14. Diagnostic accuracy of contrast-enhanced digital mammography in breast cancer detection in comparison to tomosynthesis, synthetic 2D mammography and tomosynthesis combined with ultrasound in women with dense breast.
Sudhir R; Sannapareddy K; Potlapalli A; Krishnamurthy PB; Buddha S; Koppula V
Br J Radiol; 2021 Feb; 94(1118):20201046. PubMed ID: 33242249
[TBL] [Abstract][Full Text] [Related]
15. Computer-aided diagnosis in breast tomosynthesis and chest CT.
Chan HP
Nihon Hoshasen Gijutsu Gakkai Zasshi; 2009 Jul; 65(7):968-76. PubMed ID: 19661736
[TBL] [Abstract][Full Text] [Related]
16. CAPNet: Context attention pyramid network for computer-aided detection of microcalcification clusters in digital breast tomosynthesis.
Wang J; Sun H; Jiang K; Cao W; Chen S; Zhu J; Yang X; Zheng J
Comput Methods Programs Biomed; 2023 Dec; 242():107831. PubMed ID: 37783114
[TBL] [Abstract][Full Text] [Related]
17. Few-shot learning with deformable convolution for multiscale lesion detection in mammography.
Li C; Zhang D; Tian Z; Du S; Qu Y
Med Phys; 2020 Jul; 47(7):2970-2985. PubMed ID: 32160321
[TBL] [Abstract][Full Text] [Related]
18. Local Tumor Staging of Breast Cancer: Digital Mammography versus Digital Mammography Plus Tomosynthesis.
Fontaine M; Tourasse C; Pages E; Laurent N; Laffargue G; Millet I; Molinari N; Taourel P
Radiology; 2019 Jun; 291(3):594-603. PubMed ID: 30964425
[TBL] [Abstract][Full Text] [Related]
19.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
20.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
[Next] [New Search]
