Technical Note: Iterative megavoltage CT ( MVCT ) reconstruction using block‐matching 3D‐transform ( BM 3D) regularization
| Autor: | Daniel T. O'Connor, Tianye Niu, Chunlin Yang, Hao Gao, Qihui Lyu, Yi Xue, Ke Sheng |
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| Rok vydání: | 2018 |
| Předmět: |
Male
Image quality Computer science Noise reduction 02 engineering and technology Iterative reconstruction Least squares Regularization (mathematics) Article Imaging phantom 030218 nuclear medicine & medical imaging 03 medical and health sciences Imaging Three-Dimensional 0302 clinical medicine Optical transfer function 0202 electrical engineering electronic engineering information engineering Humans Computer vision Least-Squares Analysis Image resolution Shrinkage Radon transform Phantoms Imaging business.industry Prostatic Neoplasms General Medicine Head and Neck Neoplasms 020201 artificial intelligence & image processing Artificial intelligence Tomography X-Ray Computed business Algorithms |
| Zdroj: | Medical Physics. 45:2603-2610 |
| ISSN: | 2473-4209 0094-2405 |
| Popis: | PURPOSE: Megavoltage CT (MVCT) images are noisier than kilovoltage CT (KVCT) due to low detector efficiency to high energy X-rays. Conventional denoising methods compromise edge resolution and low contrast object visibility. In this work, we incorporated Block-Matching 3D-transform shrinkage (BM3D) transformation into MVCT iterative reconstruction as non-local patch-wise regularization. METHODS: The iterative reconstruction was achieved by adding to the existing least square data fidelity objective a regularization term, formulated as the L1 norm of the BM3D transformed image. A Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) was adopted to accelerate CT reconstruction. The proposed method was compared against total variation (TV) regularization, BM3D post process method, and Filtered Back Projection (FBP). RESULTS: In the Catphan phantom study, BM3D regularization better enhances low contrast objects compared with TV regularization and BM3D post process method at the same noise level. The spatial resolution using BM3D regularization is 2.79 and 2.55 times higher than that using the TV regularization at 50% of the modulation transfer function (MTF) magnitude, for the fully sampled reconstruction and down-sampled reconstruction respectively. The BM3D regularization images show better bony details and low contrast soft tissues, on the head and neck (H&N) and prostate patient images. CONCLUSIONS: The proposed iterative BM3D regularization CT reconstruction method takes advantage of both the BM3D denoising capability and iterative reconstruction data fidelity consistency. This novel approach is superior to TV regularized iterative reconstruction or BM3D post process for improving noisy MVCT image quality. |
| Databáze: | OpenAIRE |
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