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- function D=bwdistsc(bw,aspect)
- % D=BWDISTSC(BW,ASPECT)
- % BWDISTSC computes Euclidean distance transform of the binary 3D image
- % BW. For each pixel in BW, the distance transform assignes a number
- % that is the distance between that pixel and the nearest nonzero pixel
- % of BW. BW may be a single 2D image, 3D array or a cell array of
- % 2D slices. ASPECT is 3-component vector defining aspect ratio in
- % the dataset BW. If ASPECT is not specified, isotropic aspect
- % ratio [1 1 1] is assumed.
- %
- % BWDISTSC uses fast optimized scanning algorithm and cell-arrays to
- % represent internal data, so that it is less demanding to physical
- % memory. In many cases BWDISTSC is actually faster than MATLAB's
- % optimized kd-tree algorithm used for Euclidean distance
- % transform in 3D.
- %
- % BWDISTSC tries to use MATLAB bwdist for 2D scans if possible, which
- % is significantly faster. Otherwise BWDISTSC uses internal algorithm
- % to perform 2D scans.
- %
- % Yuriy Mishchenko JFRC HHMI Chklovskii Lab JUL 2007
- % This code is free for use or modifications, just please give credit
- % where appropriate. And if you modify code or fix bugs, please drop
- % me a message at gmyuriy@hotmail.com.
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- % Scan algorithms below use following Lema: %
- % LEMA: let F(X,z) be lower envelope of a family of parabola: %
- % F(X,z)=min_{i} [G_i(X)+(z-k_i)^2]; %
- % and let H_k(X,z)=A(X)+(z-k)^2 be a parabola. %
- % Then for H_k(X,z)==F(X,z) at each X there exist at most %
- % two solutions k1<k2 such that H_k12(X,z)=F(X,z), and %
- % H_k(X,z)<F(X,z) is restricted to at most k1<k2. %
- % Here X is any-dimensional coordinate. %
- % %
- % Thus, simply scan away from any z such that H_k(X,z)<F(X,z) %
- % in either direction as long as H_k(X,z)<F(X,z) and update %
- % F(X,z). Note that need to properly choose starting point; %
- % starting point is any z such that H_k(X,z)<F(X,z); z==k is %
- % usually, but not always the starting point!!! %
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
- % parse inputs
- if(nargin<2 || isempty(aspect)) aspect=[1 1 1]; end
- % determine geometry of data
- if(iscell(bw)) shape=[size(bw{1}),length(bw)]; else shape=size(bw); end
- % fix to handle 1D & 2D images
- if(length(shape)<3) shape(length(shape)+1:3)=1; end
- if(length(aspect)<3) aspect(length(aspect)+1:3)=1; end
- % allocate space
- D=cell(1,shape(3)); for k=1:shape(3) D{k}=zeros(shape(1:2)); end
- %%%%%%%%%%%%% scan along XY %%%%%%%%%%%%%%%%
- for k=1:shape(3)
- if(iscell(bw)) bwXY=bw{k}; else bwXY=bw(:,:,k); end
-
- % initialize arrays
- DXY=zeros(shape(1:2));
- D1=zeros(shape(1:2));
- DK=zeros(shape(1:2));
- % if can, use 2D bwdist from image processing toolbox
- if(exist('bwdist') && aspect(1)==aspect(2))
- D1=aspect(1)^2*bwdist(bwXY).^2;
- else % if not, use full XY-scan
- %%%%%%%%%%%%%%% X-SCAN %%%%%%%%%%%%%%%
- % reference nearest bwXY "on"-pixel in x direction downward:
-
- % scan bottow-up, copy x-reference from previous row unless
- % there is bwXY "on"-pixel in that point in current row
- xlower=repmat(Inf,shape(1:2));
-
- xlower(1,find(bwXY(1,:)))=1; % fill in first row
- for i=2:shape(1)
- xlower(i,:)=xlower(i-1,:); % copy previous row
- xlower(i,find(bwXY(i,:)))=i;% unless there is pixel
- end
-
- % reference nearest bwXY "on"-pixel in x direction upward:
- xupper=repmat(Inf,shape(1:2));
-
- xupper(end,find(bwXY(end,:)))=shape(1);
- for i=shape(1)-1:-1:1
- xupper(i,:)=xupper(i+1,:);
- xupper(i,find(bwXY(i,:)))=i;
- end
-
- % find points for which distance needs to be updated
- idx=find(~bwXY); [x,y]=ind2sub(shape(1:2),idx);
-
- % set distance as the shortest to upward or to downward
- DXY(idx)=aspect(1)^2*min((x-xlower(idx)).^2,(x-xupper(idx)).^2);
-
- %%%%%%%%%%%%%%% Y-SCAN %%%%%%%%%%%%%%%
- % this will be the envelop
- % envelop is initialized at Inf to ensure single scan direction,
- % otherwise may end up in infinite loop when trying to find
- % starting point
- D1=repmat(Inf,shape(1:2));
- % these will be the references to parabolas defining the envelop
- DK=repmat(Inf,shape(1:2));
- % starting points
- i0=zeros(shape(1),1);
- % convenience x-coords array
- x=(1:shape(1))';
-
- for i=1:shape(2)
- % need to select starting point for each X:
- % * starting point should be below current envelop
- % * i0==i is not necessarily a starting point
- % * there is at most one starting point
- % * there may be no starting point
-
- % i0 is the starting points for each X: i0(X) is the first
- % y-index such that parabola from line i is below the envelop
-
- % first guess is the current y-line
- i0(:)=i;
-
- % some auxiliary datasets
- d0=DXY(:,i);
- % L0 indicates for which X starting point had been fixed
- L0=isinf(d0) | (d0==0);
-
- while(~isempty(find(~L0,1)))
- % reference starting points in DXY
- idx=sub2ind(shape(1:2),x(~L0),i0(~L0));
-
- % reduce out trivial points (DXY==0)
- L=(DXY(idx)==0);
- L0(~L0)=L;
- idx=idx(~L);
-
- if(isempty(idx)) continue; end
-
- % these are current best parabolas for starting points
- ik=DK(idx);
-
- % these are new values from parabola from line #i
- dtmp=d0(~L0)+aspect(2)^2*(i0(~L0)-i).^2;
-
- % these starting points are OK - below the envelop
- L=D1(idx)>dtmp; D1(idx(L))=dtmp(L);
-
- % points which are still above the envelop but ik==i0,
- % will not get any better, so fix them as well
- L=L | (ik==i0(~L0));
-
- % all other points are not OK, need new starting point:
- % starting point should be at least below parabola
- % beating us at current choice of i0
-
- % solve quadratic equation to find where this happens
- ik=(ik-i);
- di=(D1(idx(~L))-dtmp(~L))./ik(~L)/2/aspect(2)^2;
- % should select next highest index to the equality
- di=fix(di)+sign(di);
-
- % the new starting points
- idx=find(~L0);
- i0(idx(~L))=i0(idx(~L))+di;
- % update L0 to indicate which points we've fixed
- L0(~L0)=L; L0(idx(~L))=(di==0);
-
- % points that went out of boundaries can't get better;
- % fix them as well
- idx=idx(~L);
- idx=idx((i0(idx)<1) | (i0(idx)>shape(2)));
- i0(idx)=i;
- L0(idx)=1;
- end
- % reduce out trivial points DXY(idx)<DXY(:,i)
- idx=sub2ind(shape(1:2),x,i0);
- L=(DXY(idx)>0) | (i0==i);
- idx=idx(L);
- % these will keep track along which X should
- % keep updating distances
- map_lower=L;
- map_upper=L;
- idx_lower=idx;
- idx_upper=idx;
-
- % set trivial pixels D==0 in line #i:
- % this has to be done b/s we manually discarded them from L0
- D1(d0==0,i)=0;
- % scan from starting points for each X,i0 in increments of 1
- di=0; % distance from current y-line
- eols=2; % end-of-line-scan flag
- totlen=prod(shape(1:2));
- while(eols)
- eols=2;
- di=di+1;
-
- % select X which can be updated for di<0;
- % i.e. X which had been below envelop all way till now
- if(~isempty(idx_lower))
- % shift y by -1
- idx_lower=idx_lower-shape(1);
-
- % prevent index dropping below 1st
- L=(idx_lower>=1);
- map_lower(map_lower)=L;
- idx_lower=idx_lower(L);
-
- if(~isempty(idx_lower))
- dtmp=d0(map_lower)+...
- aspect(2)^2*(i0(map_lower)-di-i).^2;
-
- % these pixels are to be updated with i0-di
- L=D1(idx_lower)>dtmp & DXY(idx_lower)>0;
- map_lower(map_lower)=L;
- idx_lower=idx_lower(L);
- D1(idx_lower)=dtmp(L);
- DK(idx_lower)=i;
- end
- else % if this is empty, get ready to quit
- eols=eols-1;
- end
- % select X which can be updated for di>0;
- % i.e. X which had been below envelop all way till now
- if(~isempty(idx_upper))
- % shift y by +1
- idx_upper=idx_upper+shape(1);
-
- % prevent index from going over array limits
- L=(idx_upper<=totlen);
- map_upper(map_upper)=L;
- idx_upper=idx_upper(L);
-
- if(~isempty(idx_upper))
- dtmp=d0(map_upper)+...
- aspect(2)^2*(i0(map_upper)+di-i).^2;
-
- % check which pixels are to be updated with i0+di
- L=D1(idx_upper)>dtmp & DXY(idx_upper)>0;
- map_upper(map_upper)=L;
- idx_upper=idx_upper(L);
- D1(idx_upper)=dtmp(L);
- DK(idx_upper)=i;
- end
- else % if this is empty, get ready to quit
- eols=eols-1;
- end
- end
- end
- end
- D{k}=D1;
- end
- %%%%%%%%%%%%% scan along Z %%%%%%%%%%%%%%%%
- % this will be the envelop:
- % envelop has to be initialized at Inf to ensure single direction of scan,
- % otherwise may end up in infinite loop when trying to find starting point
- D1=cell(size(D));
- for k=1:shape(3) D1{k}=repmat(Inf,shape(1:2)); end
- % these will be the references to parabolas defining the envelop
- DK=cell(size(D));
- for k=1:shape(3) DK{k}=repmat(Inf,shape(1:2)); end
- % start building the envelope
- for k=1:shape(3)
- % need to select starting point for each X:
- % * starting point should be below current envelop
- % * k0==k is not necessarily a starting point
- % * there may be no starting point
-
- % k0 is the starting points for each XY: k0(XY) is the first
- % z-index such that parabola from line k is below the envelop
- % initial starting point guess is current slice
- k0=repmat(k,shape(1:2));
-
- % L0 indicates which starting points had been fixed
- L0=isinf(D{k}) | (D{k}==0);
- idxtot=find(~L0);
-
- while(~isempty(idxtot))
- % because of using cells need to explicitly scan in Z
- % to avoid repetitious searches in k0, parse first
- ss=getregions(k0(idxtot));
- sslen=length(ss);
-
- for kk=1:sslen
- % these are starting points @kk which had not been set
- idx=idxtot(ss(kk).PixelIdxList);
-
- % reduce out trivial points (D==0)
- if(kk~=k)
- L=(D{kk}(idx)==0);
- L0(idx)=L;
- idx=idx(~L);
- end
- if(isempty(idx)) continue; end
-
- % these are currently best parabolas for slice kk
- ik=DK{kk}(idx);
-
- % these are new values for slice kk from parabola from k
- dtmp=D{k}(idx)+aspect(3)^2*(kk-k)^2;
-
- % these points are OK - below current envelop
- L=D1{kk}(idx)>dtmp; D1{kk}(idx(L))=dtmp(L);
-
- % these points are not OK, but since ik==k0
- % can't get any better
- L=L | (ik==kk);
-
- % all other points are not OK, need new starting point:
- % starting point should be at least below parabola
- % beating us at current choice of k0
-
- % solve quadratic equation to find where this happens
- ik=(ik-k);
- dk=(D1{kk}(idx(~L))-dtmp(~L))./ik(~L)/2/aspect(3)^2;
- dk=fix(dk)+sign(dk);
- k0(idx(~L))=k0(idx(~L))+dk;
-
- % update starting points that had been set
- L0(idx)=L;
- L0(idx(~L))=(dk==0);
-
- % points that went out of boundaries can't get better
- idx=idx(~L);
- idx=idx((k0(idx)<1) | (k0(idx)>shape(3)));
- L0(idx)=1;
- k0(idx)=k;
- end
- idxtot=find(~L0);
- end
-
- % map_lower/map_upper keeps track of which pixels can be yet updated
- % with new distance, i.e. all such XY that had been below envelop for
- % all dk up to now for dk<0/dk>0 respectively
- map_lower=true(shape(1:2));
- map_upper=true(shape(1:2));
- % parse different values in k0 to avoid repetitious searching below
- ss=getregions(k0);
- sslen=length(ss);
- % reduce out trivially faulty starting points
- for kk=1:sslen
- if(kk==k) continue; end
-
- idx=ss(kk).PixelIdxList;
-
- L=D{kk}(idx)>D{k}(idx);
- map_lower(idx)=L;
- map_upper(idx)=L;
- end
-
- % these are maintained to keep fast track of whether maps are empty
- idx_lower=find(map_lower);
- idx_upper=find(map_upper);
-
- % set trivial pixels D==0 in slice k:
- % this has to be done b/s we manually discarded them from L0
- D1{k}(D{k}==0)=0;
- % scan away from starting points in increments of 1
- dk=0; % distance from current xy-slice
- eols=2; % end-of-scan flag
- while(eols)
- eols=2;
- dk=dk+1;
- if(~isempty(idx_lower))
- % prevent index from going over the boundaries
- L=(k0(map_lower)-dk>=1);
- map_lower(map_lower)=L;
- % need to explicitly scan in Z because of using cell-arrays
- for kk=1:sslen-dk
- % get all XY such that k0-dk==kk
- idx=ss(kk+dk).PixelIdxList;
- L=map_lower(idx);
- idx=idx(L);
- if(~isempty(idx))
- dtmp=D{k}(idx)+aspect(3)^2*(kk-k)^2;
-
- % these pixels are to be updated with k0-dk
- L=D1{kk}(idx)>dtmp & D{kk}(idx)>0;
- map_lower(idx)=L;
- D1{kk}(idx(L))=dtmp(L);
-
- % ridiculously, but this is faster than
- % direct assignment
- dtmp=idx(L);
- dtmp(:)=k;
- DK{kk}(idx(L))=k;
- end
- end
- idx_lower=idx_lower(map_lower(idx_lower));
- else
- eols=eols-1;
- end
- if(~isempty(idx_upper))
- % prevent index from going over the boundaries
- L=(k0(map_upper)+dk<=shape(3));
- map_upper(map_upper)=L;
- % need to explicitly scan in Z because of using cell-arrays
- for kk=dk+1:min(shape(3),sslen+dk)
- % get all XY such that k0+dk==kk
- idx=ss(kk-dk).PixelIdxList;
- L=map_upper(idx);
- idx=idx(L);
- if(~isempty(idx))
- dtmp=D{k}(idx)+aspect(3)^2*(kk-k)^2;
-
- % these pixels are to be updated with k0+dk
- L=D1{kk}(idx)>dtmp & D{kk}(idx)>0;
- map_upper(idx)=L;
- D1{kk}(idx(L))=dtmp(L);
-
- dtmp=idx(L);
- dtmp(:)=k;
- DK{kk}(idx(L))=dtmp;
- end
- end
- idx_upper=idx_upper(map_upper(idx_upper));
- else
- eols=eols-1;
- end
- end
- end
- % the answer
- if(iscell(bw))
- D=cell(size(bw));
- for k=1:shape(3) D{k}=sqrt(D1{k}); end
- else
- D=zeros(shape);
- for k=1:shape(3) D(:,:,k)=sqrt(D1{k}); end
- end
- function s=getregions(map)
- % this function is replacer for regionprops(map,'PixelIdxList');
- % it produces the list of different values along with list of
- % indexes of pixels in map with these values; 's' is struct-array
- % such that s(i).PixelIdxList contains list of pixels in map
- % with value i.
- % enable using regionprops if available, faster on 7.3
- fregionprops=1;
- % version control for using regionprops
- v=version; v=str2num(v(1:3));
- fregionprops=fregionprops & v>=7.3;
- % in later matlab regionprops is actually faster than this code
- if(exist('regionprops') & fregionprops)
- s=regionprops(map,'PixelIdxList');
- return
- end
- idx=(1:prod(size(map)))';
- dtmp=double(map(:));
- [dtmp,ind]=sort(dtmp);
- idx=idx(ind);
- ind=[0;find([diff(dtmp(:));1])];
- s=[];
- for i=2:length(ind)
- if(dtmp(ind(i)))==0 continue; end
- s(dtmp(ind(i))).PixelIdxList=idx(ind(i-1)+1:ind(i));
- end
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