Published November 1, 2019 | Version v1
Journal article

Large cells cancer volumetry in chest computed tomography pulmonary images

  • 1. Facultad de Ciencias, Universidad de Los Andes, San Cristobal (Venezuela, Bolivarian Republic of)
  • 2. Facultad de Ciencias Básicas y Biomédicas, Universidad Simón Bolívar, San José de Cúcuta (Colombia)

Description

Lung cancer is the leading oncological cause of death in the world. As for carcinomas, they represent between 90% and 95% of lung cancers; among them, non-small cell lung cancer is the most common type and the large cell carcinoma, the pathology on which this research focuses, is usually detected with the computed tomography images of the thorax. These images have three big problems: noise, artifacts and low contrast. The volume of the large cell carcinoma is obtained from the segmentations of the cancerous tumor generated, in a semi-automatic way, by a computational strategy based on a combination of algorithms that, in order to address the aforementioned problems, considers median and gradient magnitude filters and an unsupervised grouping technique for generating the large cell carcinoma morphology. The results of high correlation between the semi-automatic segmentations and the manual ones, drawn up by a pulmonologist, allow us to infer the excellent performance of the proposed technique. This technique can be useful in the detection and monitoring of large cell carcinoma and if it is considering this kind of computational strategy, medical specialists can establish the clinic or surgical actions oriented to address this pulmonary pathology. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1742-6596/1414/1/012018

Additional details

Publishing Information

Journal Title
Journal of Physics. Conference Series (Online)
Journal Volume
1414
Journal Issue
1
Journal Page Range
[6 p.]
ISSN
1742-6596

Conference

Title
5. International Conference Days of Applied Mathematics
Dates
15-17 May 2019
Place
Barranquilla (Colombia)

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
53067664
Subject category
S62: RADIOLOGY AND NUCLEAR MEDICINE;
Resource subtype / Literary indicator
Conference
Descriptors DEI
ALGORITHMS; CARCINOMAS; CHEST; COMPUTERIZED TOMOGRAPHY; DETECTION; FILTERS; IMAGES; LUNGS; MONITORING; MORPHOLOGY; NOISE; PATHOLOGY; PERFORMANCE
Descriptors DEC
BODY; DIAGNOSTIC TECHNIQUES; DISEASES; MATHEMATICAL LOGIC; NEOPLASMS; ORGANS; RESPIRATORY SYSTEM; TOMOGRAPHY