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aca-localization-classification

在UBM图像中，首先自动定位房角隐窝的顶点，然后拟合出房角内侧边缘，并计算出房角隐窝角度、定性分析虹膜形态以及虹膜根部灰度特征等参数，最后基于Spaeth分级法将前房角分为开闭窄三类。

accurate-localization-of-key-points-scleral-spur-based-on-vgg19-on-aca-and-measurement-of-relevant

In previous studies, classification tasks were completed, and the ACA was divided into three categories: open, closed, and narrow. However, it is important to locate the scleral-spur of open angle and narrow angle and measure the relevant parameters.

ai-lab

This repository contains a docker image that I use to develop my artificial intelligence applications in an uncomplicated fashion. Python, TensorFlow, PyTorch, ONNX, Keras, OpenCV, TensorRT, Numpy, Jupyter notebook... :whale2::fire:

automatic-recognition-of-lung-opacities-region-on-chest-radiographs

肺部不透明区域识别Chest radiograph (CXR) is one of the common radiological examinations used to screen and diagnose many lung diseases. Most pulmonary diseases usually present on CXR as one or more opacities or less transparent areas of the lung. However, it is a difficult task to identify opacities areas accurately. This project designs an algorithm to assist clinicians in diagnosis.

back-propagation-neural-network-classification-algorithm-of-ecg-signal

In the ECG automatic classification system, the accuracy of classification has always been an important part of scholars'research. Therefore, BP neural network is used to classify and recognize ECG signals in ECG automatic classification system.

batchgenerators

A framework for data augmentation for 2D and 3D image classification and segmentation

bet

Bet for CT

classify-for-cervical

pytorch宫颈图像分类

code-of-learn-deep-learning-with-pytorch

This is code of book "Learn Deep Learning with PyTorch"

ct_bet

Robust Brain Extraction Tool for CT Head Images

ctseg

Brain CT segmentation and normalisation, implemented in MATLAB.

data-augmentation

dataset

医学影像数据集列表

deep-learning-with-simulated-data-in-vascular-segmentation

Brain vessel segmentation program based on Residual UNet

deep-reinforced-tree-traversal

deepcenterline

Model for finding a centerline distance map of blood vessel segmentations to then be fed into a graph minimum path extractor to find the centerlines of a vessel using PyTorch. It uses a Residual UNet (Convolutional AutoEncoder) type architecture.

distance-of-point_to_point

Distance of a pair of opposite_point

fae

FeAture Explorer

faster_rcnn_for_open_images_dataset_keras

Faster R-CNN for Open Images Dataset by Keras

fastsurfer

PyTorch implementation of FastSurferCNN

glia-net

A segmentation network for intracranial aneurysm on CTA images using pytorch

iris-location-algorithm

A method of gray value of unit sector area is proposed to solve the problem of iris localization.First, in this method, a rectangular area containing pupil is segmented by gray-scale projection algorithm, meanwhile,the OTSU algorithm is used to determine the threshold of this rectangular area and segment the pupil. With respect to outer location in a certain direction, a sector area in the direction needs to be segmented according to the pupil center. Then the gray value of each concentric sector ring is calculated by setting steps to 5 pixels,and the abscissa values of the position where the maximum change in gray value is calculated as the radius in that direction.The location of boundary points in other directions is also applied by this method.Finally, these points are filtered and used to fit outer boundary of iris. The results shows that the iris image segmented by this method can achieve good result with good application and reference value.

itkelastix

An ITK Python interface to elastix, a toolbox for rigid and nonrigid registration of images

itkminimalpathextraction

Vessel and tube centerline extraction

mra_blood_vessel_segmentation

Cerebral MRA Blood Vessel Segmentation, using Image Projections and Neural Networks

nndetection

nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.

org-atlases

ORG Fiber Clustering White Matter Atlas

pytorch-doc-zh

Pytorch 中文文档

pytorch-lesson-zh

pytorch 包教不包会

raster-images

栅格化图像算法，优化标注边缘