Recent advances in medical image processing for the evaluation of chronic kidney disease

•We propose a survey covering qualitative and quantitative analysis applied on novel medical imaging techniques to evaluate renal function.•First, we summarize the use of different imaging modalities (MRI, UE, CT, PET and SPECT) in CKD diagnosis.•We show the power of AI to guide renal dysfunction di...

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Veröffentlicht in:	Medical image analysis Jg. 69; S. 101960
Hauptverfasser:	Alnazer, Israa, Bourdon, Pascal, Urruty, Thierry, Falou, Omar, Khalil, Mohamad, Shahin, Ahmad, Fernandez-Maloigne, Christine
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 01.04.2021 Elsevier BV Elsevier
Schlagworte:	Artificial intelligence Automatic renal segmentation Chronic kidney disease Computed tomography Computer Science Deep learning Diagnosis Evaluation Heterogeneity Image processing Image segmentation Imaging techniques Kidney diseases Kidneys Learning algorithms Machine learning Magnetic resonance imaging Medical imaging Positron emission Predictions Qualitative analysis Renal function Scintigraphy Signal and Image Processing Single photon emission computed tomography Structure-function relationships Textural analysis Texture Tomography Deep learning Chronic kidney disease Textural analysis Automatic renal segmentation
ISSN:	1361-8415, 1361-8423, 1361-8423
Online-Zugang:	Volltext
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