深度学习-计算机视觉(CV)-医学图像分割

前言

记录一下研究生阶段的研究方向(医学图像分割)所看的论文以及所使用的数据集资源.

每日会对内容进行更新补充！

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一、论文

1. 15篇CV领域经典论文

(1)Receptive fields, binocular interaction and functional architecture in the cat's visual cortex

(2)Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position

(3) Gradient-based learning applied to document recognition

(4) Reducing the dimensionality of data with neural networks

(5) ImageNet Classification with Deep Convolutional Neural Networks

(6)Visualizing and understanding convolutional networks

(7) Very Deep Convolutional Networks for Large-Scale Image Recognition

(8) Network in network

(9) Going deeper with convolutions

(10) Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

(11) Deep Residual Learning for Image Recognition

(12) Xception: Deep Learning With Depthwise Separable Convolutions

(13) DenseNet: Implementing Efficient ConvNet Descriptor Pyramids

(14) Mobilenets: Efficient convolutional neural networks for mobile vision applications

(15) Learning Transferable Architectures for Scalable Image Recognition

2.图像分割方向值得关注的模型及论文

(1)ViT: An image is worth 16x16 words: Transformers for image recognition at scale

(2)SwinUnter: Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis

(3)DAU-Net: DAU-Net: A Regression Cell Counting Method

(4)TransBTS: TransBTS: Multimodal Brain Tumor Segmentation Using Transformer

(5)TransUNet: