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Artificial intelligence in computer-aided diagnosis of abdomen diseases

Artificial intelligence in computer-aided diagnosis of abdomen diseases
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摘要 The abdomen contains many organs, along with a range of abdominal diseases that require accurate diagnosis. Clinical imaging plays a crucial role in abdominal disease diagnosis, prognosis, and treatment assessment. For decades, physicists have focused on innovation in terms of imaging techniques, assisting radiologists to improve abdominal diseases detection and diagnosis. Consequently, many new imaging methods for abdominal organs have been developed, including computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), X-ray, endoscopy, and ultrasound (McAuliffe et al., 2001;Dhawan et al., 2011). Each imaging method has its own unique features. For example, abdominal MRI can achieve the most comprehensive assessment of abdominal lesions, such as the liver, kidney and prostate (Yang et al., 2017;Wang et al., 2018;Gao et al., 2017) mainly due to its diversiform sequences, including structural imaging such as T1 weighted imaging and T2 weighted imaging, as well as diffusion imaging, perfusion imaging, arterial spin labeling and other functional imaging that reflect different functional changes.
出处 《Science China(Life Sciences)》 SCIE CAS CSCD 2019年第10期1396-1399,共4页 中国科学(生命科学英文版)
分类号 Q [生物学]
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