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Lung boundary detection for chest X-ray images classification based on GLCM and probabilistic neural networks : материалы временных коллективов

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES); Budapest, HUNGARY; Budapest, HUNGARY

Год издания: 2019

Идентификатор DOI: 10.1016/j.procs.2019.09.314

Ключевые слова: Chest X-ray imaging; balance contrast enhancement technique; BCET; lung boundary detection; gray level co-occurrence matrix; probabilistic neural network

Аннотация: Extraction of various structures from the chest X-ray (CXR) images and abnormalities classification are often performed as an initial step in computer-aided diagnosis/detection (CAD) systems. The shape and size of lungs may hold clues to serious diseases

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Издание

Журнал: KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KES 2019)

Выпуск журнала: Vol. 159

Номера страниц: 1439-1448

ISSN журнала: 18770509

Место издания: AMSTERDAM

Издатель: ELSEVIER

Персоны

  • Zotin Aleksandr (Reshetnev Siberian State Univ Sci & Technol, 31 Krasnoyarsky Raboch Av, Krasnoyarsk 660037, Russia)
  • Hamad Yousif (Siberian Fed Univ, 79 Svobodny St, Krasnoyarsk 660041, Russia)
  • Simonov Konstantin (Inst Computat Modeling SB RAS, 50-44 Akademgorodok, Krasnoyarsk 5044, Russia)
  • Kurako Mikhail (Siberian Fed Univ, 79 Svobodny St, Krasnoyarsk 660041, Russia)

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