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Yin Hanlong's Projects

ailearning icon ailearning

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

bus-gan icon bus-gan

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

bus-segmentation-project icon 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 icon bus_deep_learning

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

cs-notes icon 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 icon ddad

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

face_classification icon face_classification

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

kidney-stone-detection icon 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.

minisom icon minisom

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

python-image-feature-extraction icon 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。

radiomics-research-by-using-python icon 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.

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