Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Sheng-dong NIE"'
Publikováno v:
Chinese Journal of Magnetic Resonance, Vol 39, Iss 03, Pp 366-380 (2022)
In recent years, the generative adversarial network (GAN) has attracted widespread attention with its unique adversarial training mechanism. Its applications have gradually extended to the field of medical imaging, and much excellent research has eme
Externí odkaz:
https://doaj.org/article/db0780d4c6cb4ce6aa8f539e0426c33d
Publikováno v:
Chinese Journal of Magnetic Resonance, Vol 39, Iss 02, Pp 196-207 (2022)
Accurate and reliable breast tumor segmentation is essential for the diagnosis, treatment and prognosis of breast cancer. To address the shortcomings of existing dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI)-based breast tumor segmen
Externí odkaz:
https://doaj.org/article/00abb2032b4d407192dd6485f55b9173
Publikováno v:
Chinese Journal of Magnetic Resonance, Vol 38, Iss 3, Pp 392-402 (2021)
In this paper, a new method for fine brain functional parcellation based on resting-state functional magnetic resonance imaging (rs-fMRI) data was proposed. The method combines the t-distribution stochastic neighbor embedding (t-SNE) and automatic sp
Externí odkaz:
https://doaj.org/article/c9a1eb080abd49edbf70657749730598
Autor:
Cruz, Gloria1, Sheng Dong Nie1
Publikováno v:
Journal of X-Ray Science & Technology. 2017, Vol. 25 Issue 4, p561-571. 11p.
Publikováno v:
Physica Medica. 32:1502-1509
Improving the performance of computer-aided detection (CAD) system for pulmonary nodules is still an important issue for its future clinical applications. This study aims to develop a new CAD scheme for pulmonary nodule detection based on dynamic sel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a1ec0d6f0561fdb1c5cd99a26d1eabe
https://doi.org/10.1016/j.ejmp.2016.11.001
https://doi.org/10.1016/j.ejmp.2016.11.001
Publikováno v:
Proceedings of SPIE; 1/19/2020, Vol. 11321, p1-7, 7p
Publikováno v:
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB). 46
Computer-aided detection (CAD) technology has been developed and demonstrated its potential to assist radiologists in detecting pulmonary nodules especially at an early stage. In this paper, we present a novel scheme for automatic detection of pulmon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a006577c9472b96ba896d0b1e5989df
https://pubmed.ncbi.nlm.nih.gov/29519398
https://pubmed.ncbi.nlm.nih.gov/29519398
Publikováno v:
Applied Mechanics and Materials. :3830-3834
It is common sense that CAD has great significance in the lung nodule detection. But it is still controversial whether the CAD can also automatically differentiates between malignant and benign pulmonary nodules. The primary cause of this controversy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b198a49ef98ceb6c5fa8dea169555394
https://doi.org/10.4028/www.scientific.net/amm.513-517.3830
https://doi.org/10.4028/www.scientific.net/amm.513-517.3830
Two-pass region growing combined morphology algorithm for segmenting airway tree from CT chest scans
Publikováno v:
2016 UKACC 11th International Conference on Control (CONTROL).
A method based on two passes of 3D region growing and morphological reconstruction for segmenting pulmonary airway tree from computed tomography (CT) chest scans is presented to solve the problem of leakage and under-segmentation caused by the partia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be367c268f1d6c1062978e830149186e
https://doi.org/10.1109/control.2016.7737635
https://doi.org/10.1109/control.2016.7737635
Publikováno v:
Physics in Medicine & Biology. 63:035036
This study aims to develop a computer-aided diagnosis (CADx) scheme for classification between malignant and benign lung nodules, and also assess whether CADx performance changes in detecting nodules associated with early and advanced stage lung canc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a74d548abd18bbb69d0356639c85d70
https://doi.org/10.1088/1361-6560/aaa610
https://doi.org/10.1088/1361-6560/aaa610