ArticleMagnetic resonance in medicine2023
Model-based image reconstruction with wavelet sparsity regularization for through-plane resolution restoration in T
Article in Magnetic resonance in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- The Expanding Frontier: The Role of Artificial Intelligence in Pediatric Neuroradiology.Children (Basel, Switzerland) · 2025Review
- Accelerated diffusion-weighted imaging of the prostate employing echo planar imaging with compressed SENSE based reconstruction.Scientific reports · 2025Article
- Comparison of model-based versus deep learning-based image reconstruction for thin-slice T2-weighted spin-echo prostate MRI.Abdominal radiology (New York) · 2024Article
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6 authors.
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Abstract
purposeThe purpose is to develop a model-based image-reconstruction method using wavelet sparsity regularization for maintaining restoration of through-plane resolution but with improved retention of SNR versus linear reconstruction using Tikhonov (TK) regularization in high through-plane resolution (1 mm) T
methodsA wavelet sparsity (WS)-regularized image reconstruction was developed that takes as input a set of ≈80 overlapped 3-mm-thick slices acquired using a T2SE multislice scan and typically 30 coil elements. After testing in contrast and resolution phantoms and calibration in 6 subjects, the WS reconstruction was evaluated in 16 consecutive prostate T2SE MRI exams. Results reconstructed with nominal 1-mm thickness were compared with those from the TK reconstruction with the same raw data. Results were evaluated radiologically. The ratio of magnitude of prostate signal to periprostatic muscle signal was used to assess the presence of noise reduction. Technical performance was also compared with a commercial 3D-T2SE sequence.
resultsThe new WS reconstruction was assessed as superior statistically to TK for overall SNR, contrast, and multiple evaluation criteria related to sharpness while retaining the high (1 mm) through-plane resolution. Wavelet sparsity tended to provide improved overall diagnostic quality versus TK, but not significantly so. In all 16 studies, the prostate-to-muscle signal ratio increased.
conclusionsModel-based WS-regularized reconstruction consistently provides improved SNR in high (1 mm) through-plane resolution images of prostate T2SE MRI versus linear reconstruction using TK regularization.
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