Voxel-based comparative analysis of lung lesions in CT for therapeutic purposes.

Lung cancer remains as one of the most incident types of cancer throughout the world. Temporal evaluation has become a very useful tool when one wishes to analyze some malignancy-indicating behavior. The objective of the present work is to detect changes in the local densities of lung lesions over t...

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Publicado en:Medical & Biological Engineering & Computing Vol. 55; no. 2; pp. 295 - 315
Autores principales: Netto, Stelmo, Silva, Aristófanes, Nunes, Rodolfo, Gattass, Marcelo, Netto, Stelmo Magalhães Barros, Silva, Aristófanes Corrêa, Nunes, Rodolfo Acatauassú
Formato: research Journal Article
Publicado: Springer Nature Feb2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2017
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s11517-016-1510-0
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        atl: Voxel-based comparative analysis of lung lesions in CT for therapeutic purposes.
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          Netto, Stelmo
          Silva, Aristófanes
          Nunes, Rodolfo
          Gattass, Marcelo
          Netto, Stelmo Magalhães Barros
          Silva, Aristófanes Corrêa
          Nunes, Rodolfo Acatauassú
        affil: Federal University of Maranhão - UFMA , São Luís Brazil
      sug:
        subj:
          Lung Neoplasms
          Lung
          Lung Pathology
          Tomography, X-Ray Computed Methods
          Image Processing, Computer Assisted Methods
          Human
          Resource Databases
          Logic
          Lung Neoplasms Pathology
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Scales
      ab: Lung cancer remains as one of the most incident types of cancer throughout the world. Temporal evaluation has become a very useful tool when one wishes to analyze some malignancy-indicating behavior. The objective of the present work is to detect changes in the local densities of lung lesions over time (follow-up analysis). From the detected changes, local information as well as extent region of changes can complement the studies regarding the malignant or benign nature of the lesion. Based on this idea, we attempt to use techniques that allow the observation of changes in the lesion over time, based on remote sensing techniques which highlight changes occurring in the environment. The techniques used were the image differencing, image rationing, median filtering, image regression and the fuzzy XOR operator. Based on the global measurement of change percentage in the density, we found density variations which were considered significant in a range from 2.22 to 36.57 % of the volume of the lesion. The results achieved are promising since, besides the visual aspects of the changes in density of the lung lesion over time, we managed to quantify these changes and compare them by volumetric analysis, a more commonly used technique for analysis of changes in lung lesions.
      pubtype: Academic Journal
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        Journal Article
      ougenre: Article
    language: English
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