About

Benchmarks

TREND DATASET BEST METHOD PAPER TITLE PAPER CODE COMPARE

Greatest papers with code

Enforcing temporal consistency in Deep Learning segmentation of brain MR images

13 Jun 2019bigmb/Unet-Segmentation-Pytorch-Nest-of-Unets

Proposed CNN based segmentation approaches demonstrate how 2D segmentation using prior slices can provide similar results to 3D segmentation while maintaining good continuity in the 3D dimension and improved speed.

3D MEDICAL IMAGING SEGMENTATION 4D SPATIO TEMPORAL SEMANTIC SEGMENTATION BRAIN IMAGE SEGMENTATION HIPPOCAMPUS

Machine learning for neural decoding

2 Aug 2017KordingLab/Neural_Decoding

Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods.

HIPPOCAMPUS

Continual Learning with Deep Generative Replay

NeurIPS 2017 kuc2477/pytorch-deep-generative-replay

Attempts to train a comprehensive artificial intelligence capable of solving multiple tasks have been impeded by a chronic problem called catastrophic forgetting.

CONTINUAL LEARNING GENERAL CLASSIFICATION HIPPOCAMPUS IMAGE CLASSIFICATION

Alzheimer's Disease Diagnostics by Adaptation of 3D Convolutional Network

2 Jul 2016ehosseiniasl/3d-convolutional-network

The 3D-CNN is built upon a 3D convolutional autoencoder, which is pre-trained to capture anatomical shape variations in structural brain MRI scans.

GENERAL CLASSIFICATION HIPPOCAMPUS SKULL STRIPPING

Alzheimer's Disease Diagnostics by a Deeply Supervised Adaptable 3D Convolutional Network

2 Jul 2016ehosseiniasl/3d-convolutional-network

The 3D-CNN is built upon a 3D convolutional autoencoder, which is pre-trained to capture anatomical shape variations in structural brain MRI scans.

GENERAL CLASSIFICATION HIPPOCAMPUS SKULL STRIPPING

Model-Free Episodic Control

14 Jun 2016ShibiHe/Model-Free-Episodic-Control

State of the art deep reinforcement learning algorithms take many millions of interactions to attain human-level performance.

DECISION MAKING HIPPOCAMPUS

Point process models for sequence detection in high-dimensional neural spike trains

NeurIPS 2020 lindermanlab/PPSeq.jl

Sparse sequences of neural spikes are posited to underlie aspects of working memory, motor production, and learning.

HIPPOCAMPUS

Dilated deeply supervised networks for hippocampus segmentation in MRI

20 Mar 2019satyakees/FaultNet

Tissue loss in the hippocampi has been heavily correlated with the progression of Alzheimer's Disease (AD).

HIPPOCAMPUS SEMANTIC SEGMENTATION

Stable deep neural network architectures for mitochondria segmentation on electron microscopy volumes

8 Apr 2021danifranco/EM_Image_Segmentation

For that reason, and following a recent code of best practices for reporting experimental results, we present an extensive study of the state-of-the-art deep learning architectures for the segmentation of mitochondria on EM volumes, and evaluate the impact in performance of different variations of 2D and 3D U-Net-like models for this task.

ELECTRON MICROSCOPY HIPPOCAMPUS

Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease

18 Dec 2020martindyrba/DeepLearningInteractiveVis

We trained a CNN for the detection of AD in N=663 T1-weighted MRI scans of patients with dementia and amnestic mild cognitive impairment (MCI) and verified the accuracy of the models via cross-validation and in three independent samples including N=1655 cases.

HIPPOCAMPUS