%0 Journal Article %1 ruhaiyemcerebrovascular %A Ruhaiyem, Nur Intan Raihana %A Hammade, Nur Atifah %D 2021 %J International Journal of Image Processing (IJIP) %K Angiography, Cerebral Cerebrovascular Disease. Enhancement, Magnetic Ratio, Resonance Segmentation, Signal-to-noise Small Time-of-flight Vessel %N 4 %P 48-67 %T Cerebrovascular Segmentation Based on Edge Preserving Filters Technique in Magnetic Resonance Angiography Images: A Systematic Review %U https://www.cscjournals.org/library/manuscriptinfo.php?mc=IJIP-1220 %V 15 %X Magnetic resonance angiography (MRA) is an emerging magnetic resonance imaging method for the detection and diagnosis of cerebrovascular diseases including cerebral small vessel disease (CSVD). However, the challenges to extract cerebrovascular structures are recognised, especially from the time-of flight MRA (TOF-MRA) images due to the intricate vascular structures and inherent noise. This paper presents a comprehensive review on image processing pipeline which have been successfully applied on CSVD images such as Computed Tomography (CT) scan, Computed Tomography Angiography (CTA), Digital Subtraction Angiography (DSA), Magnetic Resonance Angiography (MRA), and Magnetic Resonance Imaging (MRI), review on various denoising filters in CSVD images such as Nonlocal Mean (NLM) filter, Multiscale filter, Anisotropic Diffusion filter (ADF), Bilateral filter (BF), Smoothing filter, 3D Steerable filter, Moving Average filter, Trilateral filter, Wiener filter, Blockmatching and 3D filtering (BM3D), Non-linear quasi-Newton method (L-BFGS), and Histogram Equalization (HE). This review also features edge preserving filter (EPF) techniques to reduce noises while preserving the edges from TOF-MRA images including ADF, BF, NMF, Mean Shift filter (MSF), and Sigma filter (SF).

@article{ruhaiyemcerebrovascular, abstract = {Magnetic resonance angiography (MRA) is an emerging magnetic resonance imaging method for the detection and diagnosis of cerebrovascular diseases including cerebral small vessel disease (CSVD). However, the challenges to extract cerebrovascular structures are recognised, especially from the time-of flight MRA (TOF-MRA) images due to the intricate vascular structures and inherent noise. This paper presents a comprehensive review on image processing pipeline which have been successfully applied on CSVD images such as Computed Tomography (CT) scan, Computed Tomography Angiography (CTA), Digital Subtraction Angiography (DSA), Magnetic Resonance Angiography (MRA), and Magnetic Resonance Imaging (MRI), review on various denoising filters in CSVD images such as Nonlocal Mean (NLM) filter, Multiscale filter, Anisotropic Diffusion filter (ADF), Bilateral filter (BF), Smoothing filter, 3D Steerable filter, Moving Average filter, Trilateral filter, Wiener filter, Blockmatching and 3D filtering (BM3D), Non-linear quasi-Newton method (L-BFGS), and Histogram Equalization (HE). This review also features edge preserving filter (EPF) techniques to reduce noises while preserving the edges from TOF-MRA images including ADF, BF, NMF, Mean Shift filter (MSF), and Sigma filter (SF).}, added-at = {2022-01-26T14:21:26.000+0100}, author = {Ruhaiyem, Nur Intan Raihana and Hammade, Nur Atifah}, biburl = {https://www.bibsonomy.org/bibtex/2d4fef20ae7f4c3ca7b7a9466888a0791/cscjournals}, interhash = {97d559d183f2ae731e2163b2947c1cc7}, intrahash = {d4fef20ae7f4c3ca7b7a9466888a0791}, issn = {1985-2304}, journal = {International Journal of Image Processing (IJIP)}, keywords = {Angiography, Cerebral Cerebrovascular Disease. Enhancement, Magnetic Ratio, Resonance Segmentation, Signal-to-noise Small Time-of-flight Vessel}, language = {English}, month = {October}, number = 4, pages = {48-67}, timestamp = {2022-01-26T14:21:26.000+0100}, title = {Cerebrovascular Segmentation Based on Edge Preserving Filters Technique in Magnetic Resonance Angiography Images: A Systematic Review}, url = {https://www.cscjournals.org/library/manuscriptinfo.php?mc=IJIP-1220}, volume = 15, year = 2021 }