YiangAhead

0809zheng.github.io

郑之杰的个人网站

AiLearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

BUS-GAN

Semi-supervised Segmentation of Tumors from Breast Ultrasound Images with Attentional Generative Adversarial Network

Bus-Segmentation-Project

The goal of this project is to segment various breast ultrasound images in order to determine the location of a lesion by removing low contrast regions as well as the inherent speckle noise.

BUS_Deep_Learning

Detection of Malignant and Benign lesions in Breast Ultrasound Images using Deep Learning

CS-Notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计

DDAD

PyTorch implementation of the paper: Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays (MICCAI 2022)

Kidney-Stone-Detection

Kidney stones are pieces of solid material that occur in the urinary tract and can cause severe pain in the abdomen if the treatment gets delayed. Here, I have made a tool to detect the presence of a kidney stone using an ultrasound image so that a doctor can treat you. This was achieved by denoising and enhancing the ultrasound using various filters like Gaussian Blur, Median Blur, Laplacian Filter, and Gabor Filter. For improving the contrast in the image, I have used Adaptive Histogram Equalization. For the separation of shadow from stone, I used Watershed Segmentation. Further, marking is done to label the stone.

lihang-code

《统计学习方法》的代码实现

Medical-Image-Processing-Final-Project

Implement of Semi-Automated Detection of Breast Mass Spiculation Using Active Contour

YiangAhead/Kidney-Stone-Detection

Kidney stones are pieces of solid material that occur in the urinary tract and can cause severe pain in the abdomen if the treatment gets delayed. Here, I have made a tool to detect the presence of a kidney stone using an ultrasound image so that a doctor can treat you. This was achieved by denoising and enhancing the ultrasound using various filters like Gaussian Blur, Median Blur, Laplacian Filter, and Gabor Filter. For improving the contrast in the image, I have used Adaptive Histogram Equalization. For the separation of shadow from stone, I used Watershed Segmentation. Further, marking is done to label the stone.

YiangAhead/lihang-code

《统计学习方法》的代码实现

YiangAhead/Medical-Image-Processing-Final-Project

Implement of Semi-Automated Detection of Breast Mass Spiculation Using Active Contour

YiangAhead/0809zheng.github.io

郑之杰的个人网站

YiangAhead/AiLearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

YiangAhead/BUS-GAN

Semi-supervised Segmentation of Tumors from Breast Ultrasound Images with Attentional Generative Adversarial Network

YiangAhead/Bus-Segmentation-Project

The goal of this project is to segment various breast ultrasound images in order to determine the location of a lesion by removing low contrast regions as well as the inherent speckle noise.

YiangAhead/BUS_Deep_Learning

Detection of Malignant and Benign lesions in Breast Ultrasound Images using Deep Learning

YiangAhead/CS-Notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计

YiangAhead/DDAD

PyTorch implementation of the paper: Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays (MICCAI 2022)

YiangAhead/face_classification

Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.

YiangAhead/Medical-image-processing-

处理各种格式医疗图像的代码

YiangAhead/MedISeg

YiangAhead/minisom

:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps

YiangAhead/Python-Image-feature-extraction

Python实现提取图像的纹理、颜色特征，包含快速灰度共现矩阵（GLCM）、LBP特征、颜色矩、颜色直方图。

YiangAhead/Radiomics-research-by-using-Python

Radiomics (here mainly means hand-crafted based radiomics) contains data acquire, ROI segmentation, feature extraction, feature selection, machine learning modeling, and stastical analysis.

YiangAhead/Segmentation-Information-with-Attention-Integration-for-Classification-of-Breast-tumor-in-Ultrasound

A novel segmentation-to-classification scheme for breast ultrasound image classification

YiangAhead/sift_cv

python 实现sift算法