Supervised Enhancement Filter Applied to Fissure Detection

Neto, Edson Cavalcanti; Cortez, Paulo César; Cavalcante, T. S.; Filho, Valberto E. R. da Silva; Filho, PP; Holanda, MA

doi:10.1007/978-3-319-13117-7_87

Cited by 2 publications

(1 citation statement)

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“…In previous works [45,46,47,48,9,49,13,50], the authors have evaluated the potential of different segmentation approaches in order to tackle the automatic detection of lung nodules in images [51]. Overall, the results achieved shown that the studied techniques were competitive in terms of accuracy and processing time.…”

Section: Introductionmentioning

confidence: 99%

Automated recognition of lung diseases in CT images based on the optimum-path forest classifier

Filho

Barros

Ramalho

et al. 2017

Neural Comput & Applic

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The World Health Organization estimated that around 300 million people have asthma, and 210 million people are affected by Chronic Obstructive Pulmonary Disease (COPD). Also, it is estimated that the number of deaths from COPD increased 30% in 2015 and COPD will become the third major cause of death worldwide by 2030. These statistics about lung diseases get worse when one considers fibrosis, calcifications and other diseases. For the public health system, the early and accurate diagnosis of any pulmonary disease is mandatory for effective treatments and prevention of further deaths. In this sense, this work consists in using information from lung images to identify and classify lung diseases. Two steps are required to achieve these goals: automatically extraction of representative image features of the lungs, and recognition of the possible disease using a computational classifier.

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Section: Introductionmentioning

confidence: 99%