Medical volume data are rapidly increasing, growing from gigabytes to petabytes, which presents significant challenges in organisation, storage, transmission, manipulation, and rendering. To address the challenges, we propose an end-to-end architectu...
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
In this paper, we propose a Learning-based gEnome Codec (LEC), which is designed for high efficiency and enhanced flexibility. The LEC integrates several advanced technologies, including Group of Bases (GoB) compression, multi-stride coding and bidir...
The electrocardiogram (ECG) stands out as one of the most frequently used medical tests, playing a crucial role in the accurate diagnosis and treatment of patients. While ECG devices generate a huge amount of data, only a fraction of it holds valuabl...
PURPOSE: To assess the image quality of a modified Fast three-dimensional (Fast 3D) mode wheel with sequential data filling (mFast 3D wheel) combined with a deep learning denoising technique (Advanced Intelligent Clear-IQ Engine [AiCE]) in contrast-e...
Neural networks : the official journal of the International Neural Network Society
Nov 4, 2024
Both image denoising and watermark removal aim to restore a clean image from an observed noisy or watermarked one. The past research consists of the non-learning type with limited effectiveness or the learning types with limited interpretability. To ...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Oct 25, 2024
Accurate and automatic segmentation of medical images plays an essential role in clinical diagnosis and analysis. It has been established that integrating contextual relationships substantially enhances the representational ability of neural networks...
Neural networks : the official journal of the International Neural Network Society
Jul 22, 2024
Lossy image coding techniques usually result in various undesirable compression artifacts. Recently, deep convolutional neural networks have seen encouraging advances in compression artifact reduction. However, most of them focus on the restoration o...
Neural networks : the official journal of the International Neural Network Society
Jul 17, 2024
The increasing size of pre-trained language models has led to a growing interest in model compression. Pruning and distillation are the primary methods employed to compress these models. Existing pruning and distillation methods are effective in main...
Neural networks : the official journal of the International Neural Network Society
Jul 14, 2024
Compressed Sensing (CS) is a groundbreaking paradigm in image acquisition, challenging the constraints of the Nyquist-Shannon sampling theorem. This enables high-quality image reconstruction using a minimal number of measurements. Neural Networks' po...
Proceedings of the National Academy of Sciences of the United States of America
Jul 3, 2024
Efficient storage and sharing of massive biomedical data would open up their wide accessibility to different institutions and disciplines. However, compressors tailored for natural photos/videos are rapidly limited for biomedical data, while emerging...
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