IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
39437296
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
38906056
Advancements in Neural Networks have led to larger models, challenging implementation on embedded devices with memory, battery, and computational constraints. Consequently, network compression has flourished, offering solutions to reduce operations a...
PURPOSE: We present SCAMPI (Sparsity Constrained Application of deep Magnetic resonance Priors for Image reconstruction), an untrained deep Neural Network for MRI reconstruction without previous training on datasets. It expands the Deep Image Prior a...
Medical & biological engineering & computing
38922373
The exponential growth in data volume has necessitated the adoption of alternative storage solutions, and DNA storage stands out as the most promising solution. However, the exorbitant costs associated with synthesis and sequencing impeded its develo...
Neural networks : the official journal of the International Neural Network Society
39089153
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...
Neural networks : the official journal of the International Neural Network Society
39079378
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
39068676
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...
Proceedings of the National Academy of Sciences of the United States of America
38959033
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...
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...
IEEE/ACM transactions on computational biology and bioinformatics
39361454
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...