Medical Imaging History

            Medical Imaging is a young field.

            In 1895, Wilhelm Roentgen discovered x-rays.

            The primary focus for much of this development has been to improve the quality of the images for humans to evaluate.Only recently has computer technology become

sufficiently sophisticated to assist in the process of diagnosis.

            Early in the twentieth century, a Czech mathematician named Johann Radon dervied a transform for reconstructing corss-sectional information from a series of planar projections taken from around an object, While this powerful theory had been know for overy fifty years, the ability to compute the transform on real data was not possible until digital computers began to mature in 1970s.

           Imaging in 3D emerged in 1972 when x-ray computed tomography(CT) was developed independently by Godfrey Hounsfield and Alan Cormack. These innovators later shared the 1979 Nobel Prize in Medicine.

           While techniques for using x-rays in medical imaging were being refined, organic chemists had been exploring the uses of nuclear magnetic resonance(NMR) to analyze chemical samples. Felix Bloch and Edward Purcell were studying NMR in the mid 1940s. Together, they shared the Nobel Prize in Physics in 1952.

源码地址: https://pan.quark.cn/s/d1f41682e390 miyoubiAuto 米游社每日米游币自动化Python脚本(务必使用Python3) 8更新:更换cookie的获取地址 注意:禁止在B站、贴吧、或各大论坛大肆传播! 作者已退游,项目不维护了。 如果有能力的可以pr修复。 小引一波 推荐关注几个非常可爱有趣的女孩! 欢迎B站搜索: @嘉然今天吃什么 @向晚大魔王 @乃琳Queen @贝拉kira 第三方库 食用方法 下载源码 在Global.py中设置米游社Cookie 运行myb.py 本地第一次运行时会自动生产一个文件储存cookie,请勿删除 当前仅支持单个账号! 获取Cookie方法 浏览器无痕模式打开 http://user.mihoyo.com/ ,登录账号 按,打开,找到并点击 按刷新页面,按下图复制 Cookie: How to get mys cookie 当触发时,可尝试按关闭,然后再次刷新页面,最后复制 Cookie。 也可以使用另一种方法: 复制代码 浏览器无痕模式打开 http://user.mihoyo.com/ ,登录账号 按,打开,找到并点击 控制台粘贴代码并运行,获得类似的输出信息 部分即为所需复制的 Cookie,点击确定复制 部署方法--腾讯云函数版(推荐! ) 下载项目源码和压缩包 进入项目文件夹打开命令行执行以下命令 xxxxxxx为通过上面方式或取得米游社cookie 一定要用双引号包裹!! 例如: png 复制返回内容(包括括号) 例如: QQ截图20210505031552.png 登录腾讯云函数官网 选择函数服务-新建-自定义创建 函数名称随意-地区随意-运行环境Python3....
###################################################################################### ### Author/Developer: Nicolas CHEN ### Filename: export.py ### Version: 1.0 ### Field of research: Deep Learning in medical imaging ### Purpose: This Python script creates the CSV file from XML files. ### Output: This Python script creates the file "test.csv" ### with all data needed: filename, class_name, x1,y1,x2,y2 ###################################################################################### ### HISTORY ### Version | Date | Author | Evolution ### 1.0 | 17/11/2018 | Nicolas CHEN | Initial version ###################################################################################### import os, sys, random import xml.etree.ElementTree as ET from glob import glob import pandas as pd from shutil import copyfile annotations = glob('BCCD/Annotations/*.xml') df = [] cnt = 0 for file in annotations: #filename = file.split('/')[-1].split('.')[0] + '.jpg' #filename = str(cnt) + '.jpg' filename = file.split('\\')[-1] filename =filename.split('.')[0] + '.jpg' row = [] parsedXML = ET.parse(file) for node in parsedXML.getroot().iter('object'): blood_cells = node.find('name').text xmin = int(node.find('bndbox/xmin').text) xmax = int(node.find('bndbox/xmax').text) ymin = int(node.find('bndbox/ymin').text) ymax = int(node.find('bndbox/ymax').text) row = [filename, blood_cells, xmin, xmax, ymin, ymax] df.append(row) cnt += 1 data = pd.DataFrame(df, columns=['filename', 'cell_type', 'xmin', 'xmax', 'ymin', 'ymax']) data[['filename', 'cell_type', 'xmin', 'xmax', 'ymin', 'ymax']].to_csv('test.csv', index=False)
09-25
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