Combined 3D super-resolution, de-noising and partial volume correction for percutaneous ablation

Mark A. Pinnock; Yipeng Hu; Steve Bandula; Dean C. Barratt

doi:10.1117/12.2580853

15 February 2021 Combined 3D super-resolution, de-noising and partial volume correction for percutaneous ablation

Mark A. Pinnock, Yipeng Hu, Steve Bandula, Dean C. Barratt

Proceedings Volume 11596, Medical Imaging 2021: Image Processing; 115961A (2021) https://doi.org/10.1117/12.2580853
Event: SPIE Medical Imaging, 2021, Online Only

Abstract

Percutaneous cryoablation is becoming more popular for the treatment of renal cell carcinoma. Interventional computed tomography (iCT) is commonly used for guidance but reducing radiation dose and increasing slice thickness makes super-resolution (SR) essential for improving image quality. The proposed method takes low quality (LQ), thick slice images and converts them to high quality (HQ), thin slice images while performing denoising and partial volume correction in the z-direction. As LQ and HQ iCT images are challenging to pair up, we train a 3D U-Net equipped with an up-sampling module on simulated LQ (sLQ) data and then test on the real LQ (rLQ) images with cubic interpolation and random forest as comparison. During validation on sLQ data, the U-Net outperformed interpolation and random forest (SSIM 0.9991 vs 0.9959 and 0.9985 respectively), but performance suffered when testing on the out-of-distribution rLQ images. The Dice score showed a substantial improvement when used to compare needle segmentations performed on U-Net generated images versus those from interpolation and random forest (0.4073 vs. 0.2919 and 0.3777 respectively), indicating that the U-Net is reducing the z-direction partial volume effect to a greater degree than these techniques. We have shown that a neural network trained to perform SR on simulated data outperforms interpolation and random forest on real data in terms of localisation of clinically relevant objects such as needles, despite the differing data distribution.

Conference Presentation

Citation Download Citation

Mark A. Pinnock, Yipeng Hu, Steve Bandula, and Dean C. Barratt "Combined 3D super-resolution, de-noising and partial volume correction for percutaneous ablation", Proc. SPIE 11596, Medical Imaging 2021: Image Processing, 115961A (15 February 2021); https://doi.org/10.1117/12.2580853

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