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Artificial intelligence in biomedical imaging

We are pleased to present a new Special Issue on Artificial Intelligence in biomedical imaging. Artificial intelligence is increasingly used in various fields of life. One such area is medicine. Modern medical imaging provides an increasing number of features derived from different types of analysis,  including artificial intelligence. These features are most often used for a variety of analyses including fuzzy logic, evolutionary calculations, neural networks, or artificial life. Proper image processing, appropriate selection of features and artificial intelligence method can support medical diagnostics. This area has been in recent years the subject of many research papers and research grants. Consequently, this Special Issue is devoted to the subject of artificial intelligence, in its broadest sense, in biomedical engineering with particular emphasis on medical imaging. Therefore, I invite  authors who deal with new and modified machine learning methods, evolutionary calculations and their new applications in biomedical imaging. I hope that this Special Issue will be for readers a valuable supplement to the knowledge of new artificial intelligence methods and its applications in new areas of medical imaging.

  1. Content type: Research

    Early and automatic detection of pulmonary nodules from CT lung screening is the prerequisite for precise management of lung cancer. However, a large number of false positives appear in order to increase the s...

    Authors: Patrice Monkam, Shouliang Qi, Mingjie Xu, Fangfang Han, Xinzhuo Zhao and Wei Qian

    Citation: BioMedical Engineering OnLine 2018 17:96

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  2. Content type: Book Review

    This article is a review of the book “Master machine learning algorithms, discover how they work and implement them from scratch” (ISBN: not available, 37 USD, 163 pages) edited by Jason Brownlee published by ...

    Authors: Robert Koprowski and Kenneth R. Foster

    Citation: BioMedical Engineering OnLine 2018 17:17

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  3. Content type: Research

    Ocular images play an essential role in ophthalmological diagnoses. Having an imbalanced dataset is an inevitable issue in automated ocular diseases diagnosis; the scarcity of positive samples always tends to ...

    Authors: Jiewei Jiang, Xiyang Liu, Kai Zhang, Erping Long, Liming Wang, Wangting Li, Lin Liu, Shuai Wang, Mingmin Zhu, Jiangtao Cui, Zhenzhen Liu, Zhuoling Lin, Xiaoyan Li, Jingjing Chen, Qianzhong Cao, Jing Li…

    Citation: BioMedical Engineering OnLine 2017 16:132

    Published on: