【图像分割】基于计算机视觉实现医学影像分割含GUI界面
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1 简介
在图像处理与计算机视觉领域中,图像分割被视为一项关键的技术手段。它不仅有助于提升基于图像内容的特定目标定位精度,在医学影像分析等编辑抠图等技术中也具有重要应用价值。目前虽然存在多种分割方法可供选择(如基于阈值的方法、区域增长方法等),但要实现一个能在不同场景下普遍适用的有效分割算法仍面临诸多技术挑战。随着计算机视觉、现代生理学、神经心理学、物体识别等领域研究的深入发展,在智能系统开发方面具有重要理论价值与应用前景的技术——基于视觉注意机制的图像分割技术正受到广泛关注并被深入研究。这项技术不仅属于国际前沿课题之一,在遥感气象服务、医学影像分析、机械制造自动化生产流程优化等领域均展现出广阔的前景与应用潜力。本文将重点探讨如何利用计算机视觉技术实现医学影像的有效分割(如MRI成像数据中的肿瘤区域识别)。
2 部分代码
function varargout = brain_ysw(varargin)% BRAIN_YSW MATLAB code for brain_ysw.fig% BRAIN_YSW, by itself, creates a new BRAIN_YSW or raises the existing% singleton*.%% H = BRAIN_YSW returns the handle to a new BRAIN_YSW or the handle to% the existing singleton*.%% BRAIN_YSW('CALLBACK',hObject,eventData,handles,...) calls the local% function named CALLBACK in BRAIN_YSW.M with the given input arguments.%% BRAIN_YSW('Property','Value',...) creates a new BRAIN_YSW or raises the% existing singleton*. Starting from the left, property value pairs are% applied to the GUI before brain_ysw_OpeningFcn gets called. An% unrecognized property name or invalid value makes property application% stop. All inputs are passed to brain_ysw_OpeningFcn via varargin.%% *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one% instance to run (singleton)".%% See also: GUIDE, GUIDATA, GUIHANDLES% Edit the above text to modify the response to help brain_ysw% Last Modified by GUIDE v2.5 10-Jun-2015 13:34:14% Begin initialization code - DO NOT EDITgui_Singleton = 1;gui_State = struct('gui_Name', mfilename, ... 'gui_Singleton', gui_Singleton, ... 'gui_OpeningFcn', @brain_ysw_OpeningFcn, ... 'gui_OutputFcn', @brain_ysw_OutputFcn, ... 'gui_LayoutFcn', [] , ... 'gui_Callback', []);if nargin && ischar(varargin{1}) gui_State.gui_Callback = str2func(varargin{1});endif nargout [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});else gui_mainfcn(gui_State, varargin{:});end% End initialization code - DO NOT EDIT% --- Executes just before brain_ysw is made visible.function brain_ysw_OpeningFcn(hObject, eventdata, handles, varargin)% This function has no output args, see OutputFcn.% hObject handle to figure% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% varargin command line arguments to brain_ysw (see VARARGIN)% Choose default command line output for brain_yswhandles.output = hObject;% Update handles structureguidata(hObject, handles);% UIWAIT makes brain_ysw wait for user response (see UIRESUME)% uiwait(handles.figure1);% --- Outputs from this function are returned to the command line.function varargout = brain_ysw_OutputFcn(hObject, eventdata, handles) % varargout cell array for returning output args (see VARARGOUT);% hObject handle to figure% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% Get default command line output from handles structurevarargout{1} = handles.output;% --- Executes on button press in pushbutton1.function pushbutton1_Callback(hObject, eventdata, handles)% hObject handle to pushbutton1 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)warning offglobal im_org dataload('data.mat'); % 加载MRI图像数据,整个头颅图像num = str2num(get(handles.edit1,'string'));% 从13 - 31 (32-44取反)if num <13 || num>31 msgbox('num数字不对!num在13-31之间!!!');endim_org = data(:,:,num); % 第 i 帧图像axes(handles.axes1)imshow(im_org);title('原始图像'); % 显示原图像% --- Executes on button press in pushbutton2.function pushbutton2_Callback(hObject, eventdata, handles)% hObject handle to pushbutton2 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)warning offglobal im_org data bwmax_level = double(max(data(:))); if size(im_org,3)==1 im = im_org;else im = rgb2gray(im_org);endim = permute(im,[3 2 1]); % 重置矩阵的维数for i=1:3 im = flipdim(im,i);endim(im<=40/255) = 0; % 剔除灰度值低的部分(脑袋和背景)im(im>=100/255) = 0; % 剔除灰度值高的部分(颅骨和其他的组织)im(:,:,1) = 0; % 剔除大脑灰白质下面的部分灰度部分blk = ones([1 7 7]); % 块操作% im = imerode(im,blk); % 腐蚀% 分离大脑脑组织lev = graythresh(double(im)/max_level) * max_level; % 阈值bw = (im>=lev); % 二值化bw = imrotate(squeeze(bw),90); % 变异复原axes(handles.axes2)imshow(bw);title('二值化图像');% --- Executes on button press in pushbutton3.function pushbutton3_Callback(hObject, eventdata, handles)% hObject handle to pushbutton3 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)axes(handles.axes2)imshow(L);title('灰白质分割图')% --- Executes on button press in pushbutton4.function pushbutton4_Callback(hObject, eventdata, handles)% hObject handle to pushbutton4 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)clc,clear,close allfunction edit1_Callback(hObject, eventdata, handles)% hObject handle to edit1 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% Hints: get(hObject,'String') returns contents of edit1 as text% str2double(get(hObject,'String')) returns contents of edit1 as a double% --- Executes during object creation, after setting all properties.function edit1_CreateFcn(hObject, eventdata, handles)% hObject handle to edit1 (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles empty - handles not created until after all CreateFcns called% Hint: edit controls usually have a white background on Windows.% See ISPC and COMPUTER.if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor')) set(hObject,'BackgroundColor','white');end
3 仿真结果


4 参考文献
[1]李灿飞. 计算机视觉中图像分割技术的研究[D]. 湖南大学, 2005.
博主简介:精通智能优化算法、神经网络模型预测以及信号处理等领域的Matlab仿真技术,并在元胞自动机、图像处理、路径规划和无人机等多个领域具备丰富的实践经验;相关matlab代码问题可随时沟通。
部分理论引用网络文献,若有侵权联系博主删除。
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