Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Haifang Qin"'
Autor:
Tianzhu Zheng, Haifang Qin
Publikováno v:
Journal of Sensors.
With the development of the times, the progress of science and technology, and the growing needs of people, more and more urban community planning chooses artificial intelligence to replace the traditional urban community planning, at the same time,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27fcbefc7d587f24b231932a5eb8400b
Publikováno v:
Medical physicsREFERENCES. 48(11)
PURPOSE This study aimed to design and evaluate a novel method for the registration of 2D lateral cephalograms and 3D craniofacial cone-beam computed tomography (CBCT) images, providing patient-specific 3D structures from a 2D lateral cephalogram wit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3cb0c29e6ca30204fe35286edf7412b4
https://pubmed.ncbi.nlm.nih.gov/34496039
https://pubmed.ncbi.nlm.nih.gov/34496039
Publikováno v:
WACV
Hashing has attracted attention in recent years due to the rapid growth of image and video data on the web. Benefiting from recent advances in deep learning, deep supervised hashing has achieved promising results for image retrieval. However, existin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d8fb14fb11b5af85c704039dfb9b71a
https://doi.org/10.1109/wacv45572.2020.9093487
https://doi.org/10.1109/wacv45572.2020.9093487
Publikováno v:
ISBI
Masseter segmentation from noisy and blurry cone-beam CT (CBCT) images is a challenging issue considering the device-specific image artefacts. In this paper, we propose a novel approach for noise reduction and masseter muscle segmentation from CBCT i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2a7ebd818941cc5ba8ed2cf345c464e
https://doi.org/10.1109/isbi.2019.8759426
https://doi.org/10.1109/isbi.2019.8759426
Autor:
Li Liu, Pengju Jiang, Jianpeng Wang, Lin Qiu, Jianhao Wang, Xiyuan Jiang, Fan Jie, Haifang Qin
Publikováno v:
Journal of Separation Science. 40:567-573
Capillary electrophoresis with fluorescence detection was utilized to probe the self-assembly between cyanine group dye labeled tetrahistidine containing peptide and CdSe/ZnS quantum dots, inside the capillary. Quantum dots and cyanine group dye labe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09e05dea0d6d9b41e9fe59197b9036fc
https://doi.org/10.1002/jssc.201601183
https://doi.org/10.1002/jssc.201601183
Autor:
Jianhao Wang, Junling Ji, Yuqin Qin, Pengju Jiang, Teng Yiwan, Lin Qiu, Haifang Qin, Ding Shumin, Li Liu
Publikováno v:
ELECTROPHORESIS. 37:2163-2169
Herein, we have developed an in-capillary assay for simultaneous detection of the assembly and disassembly of the multivalent HA tag peptide and antibody. HA tag with hexahistidine at C terminus (YPYDVPDYAG4 H6 , termed YPYDH6 ) was conjugated with q
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::085500a9a2e40ff1e9627e5eda7f1f0c
https://doi.org/10.1002/elps.201600004
https://doi.org/10.1002/elps.201600004
Publikováno v:
CVPR
The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in proposal-based instance segmentation framework. Specifically, we enhance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::76e453c2b171373c72150d6ba0f25994
http://arxiv.org/abs/1803.01534
http://arxiv.org/abs/1803.01534
Publikováno v:
Machine Learning in Medical Imaging ISBN: 9783030009182
MLMI@MICCAI
MLMI@MICCAI
Craniofacial growths and developments play an important role in treatment planning of orthopedics and orthodontics. Traditional growth studies are mainly on longitudinal growth datasets of 2D lateral cephalometric radiographs (LCR). In this paper, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f04db3459bd637e5241691587d93c8fc
https://doi.org/10.1007/978-3-030-00919-9_43
https://doi.org/10.1007/978-3-030-00919-9_43
Masseter Segmentation from Computed Tomography Using Feature-Enhanced Nested Residual Neural Network
Publikováno v:
Machine Learning in Medical Imaging ISBN: 9783030009182
MLMI@MICCAI
MLMI@MICCAI
Masticatory muscles are of significant aesthetic and functional importance to craniofacial developments. Automatic segmentation is a crucial step for shape and functional analysis of muscles. In this paper, we propose an automatic masseter segmentati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc9aef7ff443ce522e7e2ec61938c765
https://doi.org/10.1007/978-3-030-00919-9_41
https://doi.org/10.1007/978-3-030-00919-9_41
Publikováno v:
Machine Learning in Medical Imaging ISBN: 9783319673882
MLMI@MICCAI
MLMI@MICCAI
Anterior cranial base (ACB) is known as the growth-stable structure. Automatic segmentation of the ACB is a prerequisite to superimpose orthodontic inter-treatment cone-beam computed tomography (CBCT) images. The automatic ACB segmentation is still a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::122371e5b3f3458e6b0ea939e8d3d6a2
https://doi.org/10.1007/978-3-319-67389-9_15
https://doi.org/10.1007/978-3-319-67389-9_15