Denoising of 3D MR images using a voxel-wise hybrid residual MLP-CNN model to improve small lesion diagnostic confidence

TL;DR

This paper introduces a voxel-wise hybrid residual MLP-CNN model designed to denoise 3D MRI images, especially small lesions, thereby enhancing diagnostic confidence in noisy conditions.

Contribution

The paper presents a novel hybrid residual MLP-CNN architecture tailored for small lesion denoising in 3D MRI, outperforming existing methods in both quantitative and visual assessments.

Findings

Outperforms state-of-the-art denoising methods in quantitative metrics.

Improves visual quality and lesion recovery at moderate and high noise levels.

Radiologists confirm enhanced lesion detection and image clarity.

Abstract

Small lesions in magnetic resonance imaging (MRI) images are crucial for clinical diagnosis of many kinds of diseases. However, the MRI quality can be easily degraded by various noise, which can greatly affect the accuracy of diagnosis of small lesion. Although some methods for denoising MR images have been proposed, task-specific denoising methods for improving the diagnosis confidence of small lesions are lacking. In this work, we propose a voxel-wise hybrid residual MLP-CNN model to denoise three-dimensional (3D) MR images with small lesions. We combine basic deep learning architecture, MLP and CNN, to obtain an appropriate inherent bias for the image denoising and integrate each output layers in MLP and CNN by adding residual connections to leverage long-range information. We evaluate the proposed method on 720 T2-FLAIR brain images with small lesions at different noise levels. The results show the superiority of our method in both quantitative and visual evaluations on testing dataset compared to state-of-the-art methods. Moreover, two experienced radiologists agreed that at moderate and high noise levels, our method outperforms other methods in terms of recovery of small lesions and overall image denoising quality. The implementation of our method is available at https://github.com/laowangbobo/Residual_MLP_CNN_Mixer.