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InTech
Part of book or chapter of book . 2022
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Other literature type . 2022
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Other literature type . 2022
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Computational Intelligence Approaches for Enhancing Biomedical Image Processing Applications Based on Breast Cancer

مناهج الذكاء الحاسوبي لتعزيز تطبيقات معالجة الصور الطبية الحيوية بناءً على سرطان الثدي
Authors: Abdullahi, Isa,; Ibrahim, Iliyas, Iliyas; Lefami, Zarma, Muhammad;

Computational Intelligence Approaches for Enhancing Biomedical Image Processing Applications Based on Breast Cancer

Abstract

Recent advances in the cutting-edge technologies of biomedical sensing and image processing tools provide us with big data of biomedical and various types of images that can’t be processed within a finite period by professional clinicians. Various techniques for processing biomedical images comprise mathematical algorithms that extract vital diagnostic features from biomedical information and biological data. Because of the complexity and big size of the data computation, intelligence techniques have been applied in processing, visualizing, diagnostic, and classification tasks. This study will explore the effectiveness of the variously artificial intelligence approaches on biomedical signal and image processing applications. The researchers and community entirely will benefit from this study as a guide to the state-of-the-art artificial intelligence techniques for biomedical signal and image processing applications.

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Keywords

Signal processing, Radiology, Nuclear Medicine and Imaging, Artificial intelligence, Deep Learning in Medical Image Analysis, Classification of Brain Tumor Type and Grade, Image Segmentation, Pattern recognition (psychology), Data science, Big data, Medical Imaging, Image processing, Artificial Intelligence, Health Sciences, Machine learning, Image (mathematics), Data mining, Computational intelligence, Life Sciences, Computer hardware, Applications of Deep Learning in Medical Imaging, Computer-Aided Detection, Digital signal processing, Computer science, Algorithm, Neurology, Computer Science, Physical Sciences, Computation, Medical Image Analysis, Medicine, Image-Based Diagnosis, Computer vision, Medical imaging, Neuroscience

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green
hybrid
Related to Research communities
Cancer Research