forked from richardedden/Gannet3.1
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathSubSpectralAlign.m
314 lines (263 loc) · 9.49 KB
/
SubSpectralAlign.m
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
function fids = SubSpectralAlign(fids, water_flag, MRS_struct)
ii = MRS_struct.ii;
freqRange = MRS_struct.p.sw(ii)/MRS_struct.p.LarmorFreq(ii);
freq = (size(fids,1) + 1 - (1:size(fids,1))) / size(fids,1) * freqRange + 4.68 - freqRange/2;
time = (0:(MRS_struct.p.npoints(ii)-1))'/MRS_struct.p.sw(ii);
tMax = find(time <= 0.1,1,'last');
% Pre-allocate memory
if MRS_struct.p.HERMES
n = 4;
else
n = 2;
end
D = zeros(size(fids,2)/n);
w = cell(1,n);
data = complex(zeros(size(fids,1),n));
dataLim = [];
% Optimization options
lsqnonlinopts = optimoptions(@lsqnonlin);
lsqnonlinopts = optimoptions(lsqnonlinopts,'Algorithm','levenberg-marquardt','Display','off');
% Use weighted averaging to average subspectra
if strcmp(MRS_struct.p.vendor,'Siemens_rda') % if .rda data, use conventional averaging
data = fids;
else
for jj = 1:n
if MRS_struct.p.HERMES
ind = jj:n:size(fids,2);
else
ind = find(MRS_struct.fids.ON_OFF == abs(jj-2));
end
for kk = 1:size(fids,2)/n
for ll = 1:size(fids,2)/n
tmp = sum((real(fids(1:tMax,ind(kk))) - real(fids(1:tMax,ind(ll)))).^2) / 200;
if tmp == 0
D(kk,ll) = NaN;
else
D(kk,ll) = tmp;
end
end
end
d = nanmean(D);
w{jj} = 1./d.^2;
w{jj} = w{jj}/sum(w{jj});
w{jj} = repmat(w{jj}, [size(fids,1) 1]);
if water_flag
dataLim = ceil(length(ind)/3);
data(:,jj) = sum(w{jj}(:,1:dataLim) .* fids(:,ind(1:dataLim)),2);
else
data(:,jj) = sum(w{jj} .* fids(:,ind),2);
end
end
end
clear tmp
[~, data] = FlattenData(data);
% Set HERMES subexperiment indices (A, B, C, D)
if MRS_struct.p.HERMES
if ~MRS_struct.p.HERCULES
if length(MRS_struct.p.target) == 2 && all(strcmp(MRS_struct.p.target,{'GABAGlx','GSH'}))
switch MRS_struct.p.vendor
case 'GE'
subSpecInd = [3 2 1 4];
case {'Philips','Philips_data','Philips_raw'}
subSpecInd = [1 2 3 4];
case {'Siemens_twix','Siemens_rda','Siemens_dicom'}
subSpecInd = [3 1 4 2];
end
elseif length(MRS_struct.p.target) == 3 && all(strcmp(MRS_struct.p.target,{'EtOH','GABA','GSH'}))
switch MRS_struct.p.vendor
case {'Philips','Philips_data','Philips_raw'}
% throw an error for now
case {'Siemens_twix','Siemens_rda','Siemens_dicom'}
subSpecInd = [3 1 4 2];
end
end
else
switch MRS_struct.p.vendor
case {'Philips','Philips_data','Philips_raw'}
subSpecInd = [1 4 3 2];
case {'Siemens_twix','Siemens_rda','Siemens_dicom'}
subSpecInd = [3 2 1 4];
end
end
end
% Phase-correct one subspectrum so all remaining subspectra are in the same phase
if MRS_struct.p.HERMES
ind = subSpecInd(4);
else
ind = 2;
end
fids = PhaseCorrection(data, fids, freq, ind, MRS_struct);
% Average subspectra again
if strcmp(MRS_struct.p.vendor,'Siemens_rda') % if .rda data, use conventional averaging
data = fids;
else
data = WeightedAveraging(fids, data, n, water_flag, dataLim, w, MRS_struct);
end
[flatdata, data] = FlattenData(data);
% Parameters for optimization
if MRS_struct.p.HERMES
% Water
freqLim(1,:) = freq <= 4.68+0.22 & freq >= 4.68-0.22;
[~,i] = max(abs(data(freqLim(1,:), subSpecInd([2 4]))));
freq2 = freq(freqLim(1,:));
maxFreq = freq2(i);
for jj = 1:2
tmp(jj,:) = freq <= maxFreq(jj)+0.22 & freq >= maxFreq(jj)-0.22;
end
freqLim(1,:) = or(tmp(1,:), tmp(2,:));
f0 = (maxFreq(1) - maxFreq(2)) * MRS_struct.p.LarmorFreq(ii);
x0(1,:) = [f0 0];
% NAA
freqLim(2,:) = freq <= 2.01+0.13 & freq >= 2.01-0.13;
[~,i] = max(abs(data(freqLim(2,:), subSpecInd([1 4]))));
freq2 = freq(freqLim(2,:));
maxFreq = freq2(i);
for jj = 1:2
tmp(jj,:) = freq <= maxFreq(jj)+0.18 & freq >= maxFreq(jj)-0.18;
end
freqLim(2,:) = or(tmp(1,:), tmp(2,:));
f0 = (maxFreq(1) - maxFreq(2)) * MRS_struct.p.LarmorFreq(ii);
x0(2,:) = [f0 0];
else
switch MRS_struct.p.target{1}
case {'GABAGlx','Lac','EtOH'}
if std(diff(MRS_struct.spec.F0freq(ii,:))) < 0.05 % if very strong water suppression wasn't used, use residual water
freqLim = freq <= 4.68+0.22 & freq >= 4.68-0.22;
[~,i] = max(abs(data(freqLim,:)));
freq2 = freq(freqLim);
maxFreq = freq2(i);
for jj = 1:2
freqLim(jj,:) = freq <= maxFreq(jj)+0.22 & freq >= maxFreq(jj)-0.22;
end
else % if very strong water suppression was used, use Cho
freqLim = freq <= 3.2+0.09 & freq >= 3.2-0.09;
[~,i] = max(abs(data(freqLim,:)));
freq2 = freq(freqLim);
maxFreq = freq2(i);
for jj = 1:2
freqLim(jj,:) = freq <= maxFreq(jj)+0.08 & freq >= maxFreq(jj)-0.08;
end
end
case 'GSH'
% NAA
freqLim = freq <= 2.01+0.13 & freq >= 2.01-0.13;
[~,i] = max(abs(data(freqLim,:)));
freq2 = freq(freqLim);
maxFreq = freq2(i);
for jj = 1:2
freqLim(jj,:) = freq <= maxFreq(jj)+0.18 & freq >= maxFreq(jj)-0.18;
end
end
freqLim = or(freqLim(1,:), freqLim(2,:));
f0 = (maxFreq(1) - maxFreq(2)) * MRS_struct.p.LarmorFreq(ii);
x0 = [f0 0];
end
t = 0:(1/MRS_struct.p.sw(ii)):(size(fids,1)-1)*(1/MRS_struct.p.sw(ii));
% Align subspectra to each other
if MRS_struct.p.HERMES
% Water
a = max(max(max(flatdata(:,:,subSpecInd([2 4])))));
fun = @(x) objFunc(flatdata(:,:,subSpecInd([2 4]))./a, freqLim(1,:), t, x);
param(1,:) = lsqnonlin(fun, x0(1,:), [], [], lsqnonlinopts);
% NAA
a = max(max(max(flatdata(:,:,subSpecInd([1 4])))));
fun = @(x) objFunc(flatdata(:,:,subSpecInd([1 4]))./a, freqLim(2,:), t, x);
param(2,:) = lsqnonlin(fun, x0(2,:), [], [], lsqnonlinopts);
ind = subSpecInd(1):4:size(fids,2);
for jj = 1:length(ind)
fids(:,ind(jj)) = fids(:,ind(jj)) .* exp(1i*param(2,1)*2*pi*t') * exp(1i*pi/180*param(2,2));
end
for jj = 1:4
ind = jj:4:size(fids,2);
if water_flag
data(:,jj) = sum(w{jj}(:,1:dataLim) .* fids(:,ind(1:dataLim)),2);
else
data(:,jj) = sum(w{jj} .* fids(:,ind),2);
end
end
[flatdata, data] = FlattenData(data);
% Cho
freqLim(3,:) = freq <= 3.2+0.09 & freq >= 3.2-0.09;
[~,i] = max(abs(data(freqLim(3,:), subSpecInd([3 1]))));
freq2 = freq(freqLim(3,:));
maxFreq = freq2(i);
for jj = 1:2
tmp(jj,:) = freq <= maxFreq(jj)+0.08 & freq >= maxFreq(jj)-0.08;
end
freqLim(3,:) = or(tmp(1,:), tmp(2,:));
f0 = (maxFreq(1) - maxFreq(2)) * MRS_struct.p.LarmorFreq(ii);
x0(3,:) = [f0 0];
a = max(max(max(flatdata(:,:,subSpecInd([3 1])))));
fun = @(x) objFunc(flatdata(:,:,subSpecInd([3 1]))./a, freqLim(3,:), t, x);
param(3,:) = lsqnonlin(fun, x0(3,:), [], [], lsqnonlinopts);
else
a = max(max(max(flatdata)));
fun = @(x) objFunc(flatdata./a, freqLim, t, x);
param = lsqnonlin(fun, x0, [], [], lsqnonlinopts);
end
% Apply frequency and phase corrections to subspectra
if MRS_struct.p.HERMES
ind1 = subSpecInd(2):4:size(fids,2);
ind2 = subSpecInd(3):4:size(fids,2);
for jj = 1:length(ind1)
fids(:,ind1(jj)) = fids(:,ind1(jj)) .* exp(1i*param(1,1)*2*pi*t') * exp(1i*pi/180*param(1,2));
fids(:,ind2(jj)) = fids(:,ind2(jj)) .* exp(1i*param(3,1)*2*pi*t') * exp(1i*pi/180*param(3,2));
end
else
ind = find(MRS_struct.fids.ON_OFF == 1);
for jj = 1:length(ind)
fids(:,ind(jj)) = fids(:,ind(jj)) .* exp(1i*param(1)*2*pi*t') * exp(1i*pi/180*param(2));
end
end
if ishandle(44)
close(44);
end
if ishandle(3)
close(3);
end
end
function [flatdata, data] = FlattenData(data)
flatdata(:,1,:) = real(data);
flatdata(:,2,:) = imag(data);
data = real(fftshift(fft(data,[],1),1));
end
function fids = PhaseCorrection(data, fids, freq, ind, MRS_struct)
OFF = data(:,ind);
ii = MRS_struct.ii;
freqLim = freq <= 3.02+0.15 & freq >= 3.02-0.15;
[~,i] = max(abs(OFF(freqLim)));
freq2 = freq(freqLim);
maxFreq = freq2(i);
freqLim = freq <= maxFreq+0.58 & freq >= maxFreq-0.42;
OFF = OFF(freqLim);
Baseline = (OFF(1) + OFF(end))/2;
Width = 0.05;
Area = (max(OFF) - min(OFF)) * Width * 4;
x0 = [Area Width maxFreq 0 Baseline 0 1] .* [1 2*MRS_struct.p.LarmorFreq(ii) MRS_struct.p.LarmorFreq(ii) 180/pi 1 1 1];
ModelParamChoCr = FitChoCr(freq(freqLim), OFF, x0, MRS_struct.p.LarmorFreq(ii));
fids = fids * exp(1i*pi/180*ModelParamChoCr(4));
end
function data = WeightedAveraging(fids, data, n, water_flag, dataLim, w, MRS_struct)
for ii = 1:n
if MRS_struct.p.HERMES
ind = ii:4:size(fids,2);
else
ind = find(MRS_struct.fids.ON_OFF == abs(ii-2));
end
if water_flag
data(:,ii) = sum(w{ii}(:,1:dataLim) .* fids(:,ind(1:dataLim)),2);
else
data(:,ii) = sum(w{ii} .* fids(:,ind),2);
end
end
end
function out = objFunc(in, freqLim, t, x)
f = x(1);
phi = x(2);
y = complex(in(:,1,1), in(:,2,1));
y = y .* exp(1i*pi*(t'*f*2+phi/180));
a = real(fftshift(fft(y)));
b = real(fftshift(fft(complex(in(:,1,2), in(:,2,2)))));
DIFF = a - b;
out = DIFF(freqLim);
end