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Performance of low-dose CT image reconstruction for detecting intracerebral hemorrhage: selection of dose, algorithms and their combinations / 南方医科大学学报
Journal of Southern Medical University ; (12): 223-231, 2022.
Article in Chinese | WPRIM | ID: wpr-936305
ABSTRACT
OBJECTIVE@#To investigate the performance of different low-dose CT image reconstruction algorithms for detecting intracerebral hemorrhage.@*METHODS@#Low-dose CT imaging simulation was performed on CT images of intracerebral hemorrhage at 30%, 25% and 20% of normal dose level (defined as 100% dose). Seven algorithms were tested to reconstruct low-dose CT images for noise suppression, including filtered back projection algorithm (FBP), penalized weighted least squares-total variation (PWLS-TV), non-local mean filter (NLM), block matching 3D (BM3D), residual encoding-decoding convolutional neural network (REDCNN), the FBP convolutional neural network (FBPConvNet) and image restoration iterative residual convolutional network (IRLNet). A deep learning-based model (CNN-LSTM) was used to detect intracerebral hemorrhage on normal dose CT images and low-dose CT images reconstructed using the 7 algorithms. The performance of different reconstruction algorithms for detecting intracerebral hemorrhage was evaluated by comparing the results between normal dose CT images and low-dose CT images.@*RESULTS@#At different dose levels, the low-dose CT images reconstructed by FBP had accuracies of detecting intracerebral hemorrhage of 82.21%, 74.61% and 65.55% at 30%, 25% and 20% dose levels, respectively. At the same dose level (30% dose), the images reconstructed by FBP, PWLS-TV, NLM, BM3D, REDCNN, FBPConvNet and IRLNet algorithms had accuracies for detecting intracerebral hemorrhage of 82.21%, 86.80%, 89.37%, 81.43%, 90.05%, 90.72% and 93.51%, respectively. The images reconstructed by IRLNet at 30%, 25% and 20% dose levels had accuracies for detecting intracerebral hemorrhage of 93.51%, 93.51% and 93.06%, respectively.@*CONCLUSION@#The performance of reconstructed low-dose CT images for detecting intracerebral hemorrhage is significantly affected by both dose and reconstruction algorithms. In clinical practice, choosing appropriate dose level and reconstruction algorithm can greatly reduce the radiation dose and ensure the detection performance of CT imaging for intracerebral hemorrhage.
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Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Image Processing, Computer-Assisted / Tomography, X-Ray Computed / Least-Squares Analysis / Cerebral Hemorrhage Limits: Humans Language: Chinese Journal: Journal of Southern Medical University Year: 2022 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Image Processing, Computer-Assisted / Tomography, X-Ray Computed / Least-Squares Analysis / Cerebral Hemorrhage Limits: Humans Language: Chinese Journal: Journal of Southern Medical University Year: 2022 Type: Article