【细胞分割】基于matlab GUI原子力显微镜图像分析【含Matlab源码 1371期】

💥💥💥💥💥💥💞💞💞💞💞💞💞💞欢迎来到海神之光博客之家💞💞💞💞💞💞💞💞💥💥💥💥💥💥
在这里插入图片描述
✅博主简介:热爱科研的Matlab仿真开发者,修心和技术同步精进;
🍎个人主页:海神之光
🏆代码获取方式:
海神之光Matlab王者学习之路—代码获取方式

⛳️座右铭:行百里者,半于九十。
更多Matlab图像处理仿真内容点击👇
Matlab图像处理(进阶版)
付费专栏Matlab图像处理(初级版)

⛳️关注优快云海神之光,更多资源等你来!!

⛄一、AFM简介

理论知识参考文献:原子力显微镜(AFM)图像的计算机辅助分析

⛄二、部分源代码

function varargout = AFManalysis(varargin)
% AFMANALYSIS M-file for AFManalysis.fig
% AFMANALYSIS, by itself, creates a new AFMANALYSIS or raises the existing
% singleton*.
%
% H = AFMANALYSIS returns the handle to a new AFMANALYSIS or the handle to
% the existing singleton*.
%
% AFMANALYSIS(‘CALLBACK’,hObject,eventData,handles,…) calls the local
% function named CALLBACK in AFMANALYSIS.M with the given input arguments.
%
% AFMANALYSIS(‘Property’,‘Value’,…) creates a new AFMANALYSIS or raises the
% existing singleton*. Starting from the left, property value pairs are
% applied to the GUI before AFManalysis_OpeningFcn gets called. An
% unrecognized property name or invalid value makes property application
% stop. All inputs are passed to AFManalysis_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 AFManalysis

% Last Modified by GUIDE v2.5 07-Dec-2010 22:56:55

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct(‘gui_Name’, mfilename, …
‘gui_Singleton’, gui_Singleton, …
‘gui_OpeningFcn’, @AFManalysis_OpeningFcn, …
‘gui_OutputFcn’, @AFManalysis_OutputFcn, …
‘gui_LayoutFcn’, [] , …
‘gui_Callback’, []);
if nargin && ischar(varargin{1})
gui_State.gui_Callback = str2func(varargin{1});
end

if 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 AFManalysis is made visible.
function AFManalysis_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 AFManalysis (see VARARGIN)

% Choose default command line output for AFManalysis
handles.output = hObject;

% Update handles structure
guidata(hObject, handles);

% UIWAIT makes AFManalysis wait for user response (see UIRESUME)
% uiwait(handles.figure1);

% — Outputs from this function are returned to the command line.
function varargout = AFManalysis_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 structure
varargout{1} = handles.output;

% — Executes on button press in pushbuttonBrowse.
function pushbuttonBrowse_Callback(hObject, eventdata, handles)
[FileName,PathName] = uigetfile(‘*.jpg’,‘Select the image file’);

if PathName ~= 0 %if user not select cancel
addpath(PathName); %add path to file search
imagearray = imread(FileName);
handles.imagesize = size(imagearray);
axes(handles.Image);
imshow(imagearray,‘InitialMagnification’,‘fit’);
%handles.imagegray = rgb2gray(imagearray);
handles.imagearray = imagearray;
guidata(hObject, handles);

end
% hObject handle to pushbuttonBrowse (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles structure with handles and user data (see GUIDATA)

% — Executes during object creation, after setting all properties.
function Image_CreateFcn(hObject, eventdata, handles)
handles.Image= hObject;
imshow(‘square.png’);
guidata(hObject, handles);
% hObject handle to Image (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called

% Hint: place code in OpeningFcn to populate Image

% — Executes on slider movement.
function sliderimthreshhold_Callback(hObject, eventdata, handles)
s = handles.imagesize;
handles.slidervalth = get(handles.sliderth,‘Value’);
handles.imagebin = im2bw(handles.imagearray, 1-handles.slidervalth);
handles.imagebin = bwareaopen(handles.imagebin, round(s(1,1)*handles.slidervalfilter));

bouparam = str2num(get(handles.boundrypara,‘string’));
h = fspecial(‘gaussian’,bouparam,bouparam);
handles.imagebin = imfilter(handles.imagebin,h);
handles.imageedge = edge(handles.imagebin);

imagewithboundry = handles.imagearray;
for i = 1:1:s(1,1)
for j = 1:1:s(1,2)
if handles.imageedge(i,j) == 1
imagewithboundry(i,j,:)= 0;

    end
end

end
%imagewithboundry = imadd(handles.imagearray(:,:,1), handles.imageedge);
imshow(imagewithboundry,‘InitialMagnification’,‘fit’);

[L, num] = bwlabel(handles.imagebin);
area = bwarea(handles.imagebin)/num;
dia = ((area*6)/pi)^(1/3);

dianm = dia*(str2num(get(handles.imagesizenm,‘string’))/s(1,1));

num = num2str(num);
set(handles.npno,‘string’,num)

areanm = (pi/6)*((dianm)^3);
areanm = num2str(areanm);
set(handles.nparea,‘string’,area)

dianm = num2str(dianm);
set(handles.npdia,‘string’,dianm)

guidata(hObject, handles);

% hObject handle to sliderimthreshhold (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,‘Value’) returns position of slider
% get(hObject,‘Min’) and get(hObject,‘Max’) to determine range of slider

% — Executes during object creation, after setting all properties.
function sliderimthreshhold_CreateFcn(hObject, eventdata, handles)
handles.sliderth = hObject;
%handles.imagebin = im2bw(handles.image,0);
guidata(hObject, handles);
% hObject handle to sliderimthreshhold (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called

% Hint: slider controls usually have a light gray background.
if isequal(get(hObject,‘BackgroundColor’), get(0,‘defaultUicontrolBackgroundColor’))
set(hObject,‘BackgroundColor’,[.9 .9 .9]);
end

% — Executes on slider movement.
function sliderremovesmallpatch_Callback(hObject, eventdata, handles)
s = handles.imagesize;
handles.slidervalth = get(handles.sliderth,‘Value’);
handles.slidervalfilter = get(handles.sliderremovesmallpatch,‘Value’);
%handles.imagebin = im2bw(handles.imagearray, 1-handles.slidervalth);
handles.imagebin2 = bwareaopen(handles.imagebin, round(s(1,1)*handles.slidervalfilter));
handles.imageedge = edge(handles.imagebin2);
imagewithboundry = handles.imagearray;
for i = 1:1:s(1,1)
for j = 1:1:s(1,2)
if handles.imageedge(i,j) == 1
imagewithboundry(i,j,:)= 0;

    end
end

end

imshow(imagewithboundry,‘InitialMagnification’,‘fit’);

[L, num] = bwlabel(handles.imagebin2);
area = bwarea(handles.imagebin)/num;
dia = ((area*6)/pi)^(1/3);

dianm = dia*(str2num(get(handles.imagesizenm,‘string’))/s(1,1));

num = num2str(num);
set(handles.npno,‘string’,num)

areanm = (pi/6)*((dianm)^3);
areanm = num2str(areanm);
set(handles.nparea,‘string’,area)

dianm = num2str(dianm);
set(handles.npdia,‘string’,dianm)

guidata(hObject, handles);

% hObject handle to sliderremovesmallpatch (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,‘Value’) returns position of slider
% get(hObject,‘Min’) and get(hObject,‘Max’) to determine range of slider

% — Executes during object creation, after setting all properties.
function sliderremovesmallpatch_CreateFcn(hObject, eventdata, handles)
handles.sliderremovesmallpatch = hObject;
handles.slidervalfilter = 0;
guidata(hObject, handles);
% hObject handle to sliderremovesmallpatch (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles empty - handles not created until after all CreateFcns called

% Hint: slider controls usually have a light gray background.
if isequal(get(hObject,‘BackgroundColor’), get(0,‘defaultUicontrolBackgroundColor’))
set(hObject,‘BackgroundColor’,[.9 .9 .9]);
end

⛄三、运行结果

在这里插入图片描述

⛄四、matlab版本及参考文献

1 matlab版本
2014a

2 参考文献
[1]王轶文,谢建明,张惠,孙啸,陆祖宏.原子力显微镜(AFM)图像的计算机辅助分析[J].山东生物医学工程. 2002,(03)

3 备注
简介此部分摘自互联网,仅供参考,若侵权,联系删除

🍅 仿真咨询
1 各类智能优化算法改进及应用

生产调度、经济调度、装配线调度、充电优化、车间调度、发车优化、水库调度、三维装箱、物流选址、货位优化、公交排班优化、充电桩布局优化、车间布局优化、集装箱船配载优化、水泵组合优化、解医疗资源分配优化、设施布局优化、可视域基站和无人机选址优化

2 机器学习和深度学习方面
卷积神经网络(CNN)、LSTM、支持向量机(SVM)、最小二乘支持向量机(LSSVM)、极限学习机(ELM)、核极限学习机(KELM)、BP、RBF、宽度学习、DBN、RF、RBF、DELM、XGBOOST、TCN实现风电预测、光伏预测、电池寿命预测、辐射源识别、交通流预测、负荷预测、股价预测、PM2.5浓度预测、电池健康状态预测、水体光学参数反演、NLOS信号识别、地铁停车精准预测、变压器故障诊断

3 图像处理方面
图像识别、图像分割、图像检测、图像隐藏、图像配准、图像拼接、图像融合、图像增强、图像压缩感知

4 路径规划方面
旅行商问题(TSP)、车辆路径问题(VRP、MVRP、CVRP、VRPTW等)、无人机三维路径规划、无人机协同、无人机编队、机器人路径规划、栅格地图路径规划、多式联运运输问题、车辆协同无人机路径规划、天线线性阵列分布优化、车间布局优化

5 无人机应用方面
无人机路径规划、无人机控制、无人机编队、无人机协同、无人机任务分配

6 无线传感器定位及布局方面
传感器部署优化、通信协议优化、路由优化、目标定位优化、Dv-Hop定位优化、Leach协议优化、WSN覆盖优化、组播优化、RSSI定位优化

7 信号处理方面
信号识别、信号加密、信号去噪、信号增强、雷达信号处理、信号水印嵌入提取、肌电信号、脑电信号、信号配时优化

8 电力系统方面
微电网优化、无功优化、配电网重构、储能配置

9 元胞自动机方面
交通流 人群疏散 病毒扩散 晶体生长

10 雷达方面
卡尔曼滤波跟踪、航迹关联、航迹融合

评论 1
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包

打赏作者

海神之光

有机会获得赠送范围1份代码

¥1 ¥2 ¥4 ¥6 ¥10 ¥20
扫码支付:¥1
获取中
扫码支付

您的余额不足,请更换扫码支付或充值

打赏作者

实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值