M-NET is an end-to-end trainable Convolutional Neural Network (CNN) architecture, for segmenting deep (human) brain structures from Magnetic Resonance Images (MRI). A novel scheme is used to learn to combine and represent 3D …

MNet is novel data-independent CNN segmentation architecture, which realizes adaptive 2D and 3D feature fusion to balance inter- and intra-slice representation, thus being robust to varying anisotropic degrees of medical datasets and helping get rid of manual architecture design.

Mar 1, 2023 · This work proposes a new ensemble segmentation model, M-Net, using an encoder-decoder network for medical image segmentation. This model incorporates multiple deep architectures to provide better results.

In this paper, we propose an end-to-end trainable Convolutional Neural Network (CNN) architecture called the M-net, for segmenting deep (human) brain structures from Magnetic Resonance Images (MRI). A novel scheme is used to learn to combine and represent 3D context information of a given slice in a 2D slice.

In this paper, we propose an end-to-end trainable Convolu-tional Neural Network (CNN) architecture called the M-net, for segmenting deep (human) brain structures from Magnetic Resonance Images (MRI). A novel scheme is used to learn to combine and represent 3D context information of a given slice in a 2D slice.

Aug 16, 2022 · In this study, these challenges are addressed by developing a shallow convolutional neural network (CNN) model with optimal configuration performing ablation study by altering layer structure and hyper-parameters and utilizing a suitable augmentation technique.

提出方法： 论文提出了一种新的网状网络（MNet），通过学习来平衡不同方向/轴之间的关系。 1） MNet通过将多维卷积深入到基本模块中，实现了大量表示过程的融合，使表示过程的选择更加灵活，从而自适应地平衡稀疏切片间信息和密集切片内信息表示。 2） MNet潜在地融合了每个基本模块内的多维特征， 同时利用2D（2D视图中容易识别区域的高分割精度）和3D（3D器官轮廓的高平滑度）表示的优势，从而获得目标区域更准确的建模。 实验结果： 在四个公共数据 …

Apr 1, 2017 · A publication called M-net, proposed a network for segmenting 14 structures using a 2D-U-Net architecture (Mehta & Sivaswamy, 2017). This method was tested on two datasets, International Brain...

Overview of the analytical model underlying MNet. (A) The MNet model includes three primary components: Knowledgebase, Algorithm, and Deployment. Their interconnected relationships are illustrated. (B) The Knowledgebase component comprises gene-metabolite pairs sourced from five primary data sources.

The official code for the paper "MNet: A Multi-Scale Network for Visible Watermark Removal." (Published in Neural Networks 183(2025) )