TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	REMOVE
Medical Image Segmentation	iSEG 2017 Challenge	HyperDenseNet	Dice Score	0.9257	# 1

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HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation

9 Apr 2018 • Jose Dolz • Karthik Gopinath • Jing Yuan • Herve Lombaert • Christian Desrosiers • Ismail Ben Ayed

Recently, dense connections have attracted substantial attention in computer vision because they facilitate gradient flow and implicit deep supervision during training. Particularly, DenseNet, which connects each layer to every other layer in a feed-forward fashion, has shown impressive performances in natural image classification tasks... (read more)

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BRAIN SEGMENTATION

IMAGE CLASSIFICATION

MEDICAL IMAGE SEGMENTATION

MULTI-MODAL IMAGE SEGMENTATION

REPRESENTATION LEARNING

SEMANTIC SEGMENTATION

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Ranked #1 on Medical Image Segmentation on iSEG 2017 Challenge

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TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	RESULT	BENCHMARK
Medical Image Segmentation	iSEG 2017 Challenge	HyperDenseNet	Dice Score	0.9257	# 1		Compare

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METHOD	TYPE
HyperDenseNet	Semantic Segmentation Models
ReLU	Activation Functions
Batch Normalization	Normalization
Convolution	Convolutions
Average Pooling	Pooling Operations
Concatenated Skip Connection	Skip Connections
Global Average Pooling	Pooling Operations
Dense Block	Image Model Blocks
Kaiming Initialization	Initialization
1x1 Convolution	Convolutions
Dropout	Regularization
Max Pooling	Pooling Operations
Softmax	Output Functions
DenseNet	Convolutional Neural Networks
Dense Connections	Feedforward Networks

HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation

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