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Lesion Segmentation

40 papers with code · Medical

Lesion segmentation is the task of segmenting out lesions from other objects in medical based images.

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Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

ECCV 2018 tensorflow/models

The former networks are able to encode multi-scale contextual information by probing the incoming features with filters or pooling operations at multiple rates and multiple effective fields-of-view, while the latter networks can capture sharper object boundaries by gradually recovering the spatial information.

IMAGE CLASSIFICATION LESION SEGMENTATION SEMANTIC SEGMENTATION

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

2 Nov 2015divamgupta/image-segmentation-keras

We show that SegNet provides good performance with competitive inference time and more efficient inference memory-wise as compared to other architectures.

LESION SEGMENTATION REAL-TIME SEMANTIC SEGMENTATION SCENE SEGMENTATION SCENE UNDERSTANDING

Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation

18 Mar 2016Kamnitsask/deepmedic

We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural Network for the challenging task of brain lesion segmentation.

3D MEDICAL IMAGING SEGMENTATION BRAIN LESION SEGMENTATION FROM MRI BRAIN TUMOR SEGMENTATION LESION SEGMENTATION

Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation

20 Feb 2018LeeJunHyun/Image_Segmentation

In this paper, we propose a Recurrent Convolutional Neural Network (RCNN) based on U-Net as well as a Recurrent Residual Convolutional Neural Network (RRCNN) based on U-Net models, which are named RU-Net and R2U-Net respectively.

IMAGE CLASSIFICATION LESION SEGMENTATION LUNG NODULE SEGMENTATION RETINAL VESSEL SEGMENTATION SEMANTIC SEGMENTATION SKIN CANCER SEGMENTATION

Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields

7 Oct 2016IBBM/Cascaded-FCN

Automatic segmentation of the liver and its lesion is an important step towards deriving quantitative biomarkers for accurate clinical diagnosis and computer-aided decision support systems.

LESION SEGMENTATION

H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes

21 Sep 2017xmengli999/H-DenseUNet

Our method outperformed other state-of-the-arts on the segmentation results of tumors and achieved very competitive performance for liver segmentation even with a single model.

AUTOMATIC LIVER AND TUMOR SEGMENTATION LESION SEGMENTATION LIVER SEGMENTATION SEMANTIC SEGMENTATION

A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation

18 Oct 2018nabsabraham/focal-tversky-unet

We propose a generalized focal loss function based on the Tversky index to address the issue of data imbalance in medical image segmentation.

LESION SEGMENTATION SEMANTIC SEGMENTATION