Terms: = Breast cancer AND FES, FPS, 2242, ENSG00000182511, P07332 AND Diagnosis
45 results:
1. Quarter-Century Transformation of Oncology: Positron Emission Tomography for Patients with breast cancer.
Ulaner GA; Vaz SC; Groheux D
PET Clin; 2024 Apr; 19(2):147-162. PubMed ID: 38177052
[TBL] [Abstract] [Full Text] [Related]
2. Atypical architectural distortion detection in digital breast tomosynthesis: a multi-view computer-aided detection model with ipsilateral learning.
Pan J; He Z; Li Y; Zeng W; Guo Y; Jia L; Jiang H; Chen W; Lu Y
Phys Med Biol; 2023 Nov; 68(23):. PubMed ID: 37918341
[No Abstract] [Full Text] [Related]
3. 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
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4. Summary: Appropriate Use Criteria for Estrogen Receptor-Targeted PET Imaging with 16α-
Ulaner GA; Mankoff DA; Clark AS; Fowler AM; Linden HM; Peterson LM; Dehdashti F; Kurland BF; Mortimer J; Mouabbi J; Moon DH; de Vries EGE
J Nucl Med; 2023 Mar; 64(3):351-354. PubMed ID: 36863779
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5. Molecular Imaging for Estrogen Receptor-Positive breast cancer: Clinical Applications of Whole Body and Dedicated breast Positron Emission Tomography.
Goodman K; Abel MK; Lawhn-Heath C; Molina-Vega J; Jones EF; Mukhtar RA
Surg Oncol Clin N Am; 2022 Oct; 31(4):569-579. PubMed ID: 36243494
[No Abstract] [Full Text] [Related]
6. Developing breast lesion detection algorithms for digital breast tomosynthesis: Leveraging false positive findings.
Hossain MB; Nishikawa RM; Lee J
Med Phys; 2022 Dec; 49(12):7596-7608. PubMed ID: 35916103
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7. PET Imaging of Estrogen Receptors for Gynecological Tumors.
Tsujikawa T; Makino A; Mori T; Tsuyoshi H; Kiyono Y; Yoshida Y; Okazawa H
Clin Nucl Med; 2022 Jul; 47(7):e481-e488. PubMed ID: 35675139
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8. Heterogeneity of bone metastases as an important prognostic factor in patients affected by oestrogen receptor-positive breast cancer. The role of combined [18F]Fluoroestradiol PET/CT and [18F]Fluorodeoxyglucose PET/CT.
Bottoni G; Piccardo A; Fiz F; Siri G; Matteucci F; Rocca A; Nanni O; Monti M; Brain E; Alberini JL; Dib B; Sacchetti GM; Saggia C; Rossi V; Harbeck N; Wuerstlein R; Degenhardt T; DeCensi A; Rollandi GA; Gennari A
Eur J Radiol; 2021 Aug; 141():109821. PubMed ID: 34139575
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9. Deep Learning for the Detection of breast cancers on Chest Computed Tomography.
Koh J; Yoon Y; Kim S; Han K; Kim EK
Clin Breast Cancer; 2022 Jan; 22(1):26-31. PubMed ID: 34078566
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10. Evaluation of deep learning detection and classification towards computer-aided diagnosis of breast lesions in digital X-ray mammograms.
Al-Antari MA; Han SM; Kim TS
Comput Methods Programs Biomed; 2020 Nov; 196():105584. PubMed ID: 32554139
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11. An experimental and algorithm-based study of the spectral features of breast cancer patients by a photodiagnosis approach.
Atif M; Devanesan S; AlSalhi MS; Masilamani V; Saleem MNA; AlShebly M; Farhat K; Hussain I; Alimgeer KS
Photodiagnosis Photodyn Ther; 2020 Sep; 31():101851. PubMed ID: 32497774
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12. Whole-Body Characterization of Estrogen Receptor Status in Metastatic breast cancer with 16α-18F-Fluoro-17β-Estradiol Positron Emission Tomography: Meta-Analysis and Recommendations for Integration into Clinical Applications.
Kurland BF; Wiggins JR; Coche A; Fontan C; Bouvet Y; Webner P; Divgi C; Linden HM
Oncologist; 2020 Oct; 25(10):835-844. PubMed ID: 32374053
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13. breast cancer: Evaluating Tumor Estrogen Receptor Status with Molecular Imaging to Increase Response to Therapy and Improve Patient Outcomes.
Grabher BJ
J Nucl Med Technol; 2020 Sep; 48(3):191-201. PubMed ID: 32111662
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14. Computer-aided tumor detection in automated breast ultrasound using a 3-D convolutional neural network.
Moon WK; Huang YS; Hsu CH; Chang Chien TY; Chang JM; Lee SH; Huang CS; Chang RF
Comput Methods Programs Biomed; 2020 Jul; 190():105360. PubMed ID: 32007838
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15. 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
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16. Ultrasonic diagnosis of breast Nodules Using Modified Faster R-CNN.
Zhang Z; Zhang X; Lin X; Dong L; Zhang S; Zhang X; Sun D; Yuan K
Ultrason Imaging; 2019 Nov; 41(6):353-367. PubMed ID: 31615352
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17.
Liu C; Gong C; Liu S; Zhang Y; Zhang Y; Xu X; Yuan H; Wang B; Yang Z
Oncologist; 2019 Dec; 24(12):e1277-e1285. PubMed ID: 31337657
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18. Deep learning with evolutionary and genomic profiles for identifying cancer subtypes.
Lin CY; Ruan P; Li R; Yang JM; See S; Song J; Akutsu T
J Bioinform Comput Biol; 2019 Jun; 17(3):1940005. PubMed ID: 31288637
[TBL] [Abstract] [Full Text] [Related]
19. Sub-10 nm Cu
Wang D; Zhang Y; Guo Q
Int J Nanomedicine; 2018; 13():7987-7996. PubMed ID: 30538472
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20. Non-linear transformations of age at diagnosis, tumor size, and number of positive lymph nodes in prediction of clinical outcome in breast cancer.
Forsare C; Bak M; Falck AK; Grabau D; Killander F; Malmström P; Rydén L; Stål O; Sundqvist M; Bendahl PO; Fernö M
BMC Cancer; 2018 Dec; 18(1):1226. PubMed ID: 30526533
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