【图像分割】基于计算机视觉实现胸部CT肺质提取附matlab代码.zip

function BW = imbinarize(I,varargin) %#codegen %imbinarize Binarize image by thresholding. % Copyright 2015-2018 The MathWorks, Inc. % Syntax % ------ % % BW = imbinarize(I) % BW = imbinarize(I,method) % BW = imbinarize(I,'adaptive',Param,Value,...) % BW = imbinarize(I,t) % % Input Specs % ----------- % % I: % real % non-sparse % 2d % uint8, uint16, uint32, int8, int16, int32, single or double % % method: % string with value: 'global' or 'adaptive' % default: 'global' % % Sensitivity: % numeric % real % non-sparse % scalar % non-negative % <= 1 % default: 0.5 % converted to double % % ForegroundPolarity: % string with value either 'bright' or 'dark' % default: 'bright' % % t: % numeric % real % non-sparse % 2d % either scalar or matrix of the same size as I % % Output Specs % ------------ % % BW: % logical % 2D matrix % same size as I % % Validate the input image validateImage(I); % Parse and validate optional inputs [isNumericThreshold,options] = parseOptionalInputs(I,varargin{:}); coder.internal.prefer_const(isNumericThreshold,options); if isNumericThreshold % BW = imbinarize(I,t) BW = binarize(I,options.t); else if strcmp(options.method,'global') % BW = imbinarize(I,'global') t = computeGlobalThreshold(I); else % BW = imbinarize(I,'adaptive',...) t = adaptthresh(I,options.sensitivity,'ForegroundPolarity',options.polarity); end BW = binarize(I,t); end %-------------------------------------------------------------------------- function BW = binarize(I,T) % Map a threshold in [0,1] to the range of the image (e.g., [-128,127]) range = getrangefromclass(I); % We need to distinguish b/w the scalar and matrix cases % to accommodate variable sizing for the threshold input if isscalar(T) BW = I > (range(1) + (range(2)-range(1))*T(1)); else BW = I > (range(1) + (range(2)-range(1))*T); end %-------------------------------------------------------------------------- function T = computeGlobalThreshold(I) % Otsu's threshold is used to compute the global threshold. We convert % floating point images to uint8 prior to computing the image histogram to % avoid issues with NaN/Inf values in the input data. im2uint8 nicely % handles these so that we get a clean histogram for otsuthresh. For other % types, we compute the histogram in the native type, using 256 bins (this % is the default in imhist). if isfloat(I) T = otsuthresh( imhist(im2uint8(I)) ); else T = otsuthresh( imhist(I) ); end %-------------------------------------------------------------------------- function validateImage(I) supportedClasses = {'uint8','uint16','uint32','int8', ... 'int16','int32','single','double'}; supportedAttribs = {'real','nonsparse','2d'}; validateattributes(I,supportedClasses,supportedAttribs,mfilename,'I'); %-------------------------------------------------------------------------- % Parse and validate optional inputs % options is a struct with the following fields: % - t: user-specified threshold % - method: string 'global' or 'adaptive' % - sensitivity: scalar in [0,1] % - polarity: string 'bright' or 'dark' % If the user has specified a threshold, then isNumericThreshold is true. function [isNumericThreshold,options] = parseOptionalInputs(I,varargin) narginchk(1,6); % Default parameters defaultMethod = 'global'; defaultSensitivity = 0.5; defaultPolarity = 'bright'; % True if the syntax used is imbinarize(I,t) isNumericThreshold = ~isempty(varargin) && ~ischar(varargin{1}); if isNumericThreshold % imbinarize(I,t) options.t = validateThreshold(varargin{1},I); coder.internal.errorIf(numel(varargin)>1, ... 'MATLAB:TooManyInputs'); else if isempty(varargin) % imbinarize(I) options.method = defaultMethod; else method = validateMethod(varargin{1}); options.method = method; if strcmp(method,defaultMethod) % imbinarize(I,'global') coder.internal.errorIf(numel(varargin)>1, ... 'MATLAB:TooManyInputs'); else % imbinarize(I,'adaptive',...) [sensitivity,polarity] = parseNameValuePairs( ... defaultSensitivity,defaultPolarity,varargin{2:end}); % Validate options.sensitivity = validateSensitivity(sensitivity); options.polarity = validatePolarity(polarity); end end end %-------------------------------------------------------------------------- function T = validateThreshold(T_,I) validateattributes(T_,{'numeric'},{'real','nonsparse','2d'}, ... mfilename,'Threshold',2); % t must be a scalar or have the same size as I coder.internal.errorIf(~isscalar(T_) && ~isequal(size(T_),size(I)), ... 'images:imbinarize:badSizedThreshold'); T = double(T_); %-------------------------------------------------------------------------- function method = validateMethod(method_) method = validatestring(method_,{'global','adaptive'},mfilename,'Method',2); %-------------------------------------------------------------------------- % Parse optional PV pairs without validating function [sensitivity,polarity] = parseNameValuePairs( ... defaultSensitivity,defaultPolarity,varargin) % Parse optional PV pairs: 'Sensitivity' and 'ForegroundPolarity' params = struct( ... 'Sensitivity', uint32(0), ... 'ForegroundPolarity',uint32(0)); options = struct( ... 'CaseSensitivity',false, ... 'StructExpand', true, ... 'PartialMatching',true); optarg = eml_parse_parameter_inputs(params,options,varargin{:}); sensitivity = eml_get_parameter_value( ... optarg.Sensitivity, ... defaultSensitivity, ... varargin{:}); polarity = eml_get_parameter_value( ... optarg.ForegroundPolarity, ... defaultPolarity, ... varargin{:}); %-------------------------------------------------------------------------- function sensitivity = validateSensitivity(sensitivity_) validateattributes(sensitivity_,{'numeric'}, ... {'real','nonsparse','scalar','nonnegative','<=',1}, ... mfilename,'Sensitivity'); sensitivity = double(sensitivity_); %-------------------------------------------------------------------------- function polarity = validatePolarity(polarity_) polarity = validatestring(polarity_,{'bright','dark'}, ... mfilename,'ForegroundPolarity');