Segmentation of the temporalis muscle from MR data

Article Properties
Cite
Ng, H. P., et al. “Segmentation of the Temporalis Muscle from MR Data”. International Journal of Computer Assisted Radiology and Surgery, vol. 2, no. 1, 2007, pp. 19-30, https://doi.org/10.1007/s11548-007-0073-9.
Ng, H. P., Hu, Q. M., Ong, S. H., Foong, K. W. C., Goh, P. S., Liu, J., & Nowinski, W. L. (2007). Segmentation of the temporalis muscle from MR data. International Journal of Computer Assisted Radiology and Surgery, 2(1), 19-30. https://doi.org/10.1007/s11548-007-0073-9
Ng, H. P., Q. M. Hu, S. H. Ong, K. W. C. Foong, P. S. Goh, J. Liu, and W. L. Nowinski. “Segmentation of the Temporalis Muscle from MR Data”. International Journal of Computer Assisted Radiology and Surgery 2, no. 1 (2007): 19-30. https://doi.org/10.1007/s11548-007-0073-9.
Ng HP, Hu QM, Ong SH, Foong KWC, Goh PS, Liu J, et al. Segmentation of the temporalis muscle from MR data. International Journal of Computer Assisted Radiology and Surgery. 2007;2(1):19-30.
Journal Categories
Medicine
Medicine (General)
Medicine
Medicine (General)
Medical physics
Medical radiology
Nuclear medicine
Medicine
Medicine (General)
Medical technology
Medicine
Surgery
Refrences
Title Journal Journal Categories Citations Publication Date
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  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
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  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
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10.1109/TIP.2005.860348 IEEE Transactions on Image Processing
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Engineering (General). Civil engineering (General)
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  • Medicine: Medicine (General): Medical technology
  • Medicine: Medicine (General): Medical physics. Medical radiology. Nuclear medicine
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  • Medicine: Medicine (General): Medical physics. Medical radiology. Nuclear medicine
  • Medicine: Medicine (General)
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  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
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Refrences Analysis
Category Category Repetition
Medicine: Medicine (General): Medical physics. Medical radiology. Nuclear medicine11
Science: Mathematics: Instruments and machines: Electronic computers. Computer science7
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks7
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics7
Medicine: Medicine (General)6
Medicine: Medicine (General): Medical technology5
Technology: Photography5
Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry5
Medicine: Dentistry2
Technology: Engineering (General). Civil engineering (General)2
Medicine: Surgery1
The category Medicine: Medicine (General): Medical physics. Medical radiology. Nuclear medicine 11 is the most frequently represented among the references in this article. It primarily includes studies from IEEE Transactions on Medical Imaging and IEEE Transactions on Image Processing. The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year
Citations
Title Journal Journal Categories Citations Publication Date
Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma

 British Journal of Cancer
  • Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens
  • Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens
  • Medicine: Medicine (General)
 13 2021
The Effect of Labeled/Unlabeled Prior Information for Masseter Segmentation

 Mathematical Problems in Engineering
  • Technology: Engineering (General). Civil engineering (General)
  • Science: Mathematics
  • Science: Mathematics
  • Technology: Engineering (General). Civil engineering (General)
  • Technology: Engineering (General). Civil engineering (General)
 2013
Automated segmentation of psoas major muscle in X-ray CT images by use of a shape model: preliminary study Radiological Physics and Technology
  • Medicine: Medicine (General): Medical physics. Medical radiology. Nuclear medicine
 15 2011
Citations Analysis
Category Category Repetition
Medicine: Medicine (General): Medical physics. Medical radiology. Nuclear medicine1
Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens1
Medicine: Medicine (General)1
Technology: Engineering (General). Civil engineering (General)1
Science: Mathematics1
The category Medicine: Medicine (General): Medical physics. Medical radiology. Nuclear medicine 1 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Automated segmentation of psoas major muscle in X-ray CT images by use of a shape model: preliminary study and was published in 2011. The most recent citation comes from a 2021 study titled Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma. This article reached its peak citation in 2021, with 1 citations. It has been cited in 3 different journals. Among related journals, the British Journal of Cancer cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year