Commit 8bdc2a60fedf36c4fa80f5cf4f49dd0d827c5b62
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Adding mips.pyx to invesalius project
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1 | +#http://en.wikipedia.org/wiki/Local_maximum_intensity_projection | |
2 | +import numpy as np | |
3 | +cimport numpy as np | |
4 | +cimport cython | |
5 | + | |
6 | +from libc.math cimport floor, ceil, sqrt, fabs | |
7 | +from cython.parallel import prange | |
8 | + | |
9 | +DTYPE = np.uint8 | |
10 | +ctypedef np.uint8_t DTYPE_t | |
11 | + | |
12 | +DTYPE16 = np.int16 | |
13 | +ctypedef np.int16_t DTYPE16_t | |
14 | + | |
15 | +DTYPEF32 = np.float32 | |
16 | +ctypedef np.float32_t DTYPEF32_t | |
17 | + | |
18 | +@cython.boundscheck(False) # turn of bounds-checking for entire function | |
19 | +def lmip(np.ndarray[DTYPE16_t, ndim=3] image, int axis, DTYPE16_t tmin, | |
20 | + DTYPE16_t tmax, np.ndarray[DTYPE16_t, ndim=2] out): | |
21 | + cdef DTYPE16_t max | |
22 | + cdef int start | |
23 | + cdef int sz = image.shape[0] | |
24 | + cdef int sy = image.shape[1] | |
25 | + cdef int sx = image.shape[2] | |
26 | + | |
27 | + # AXIAL | |
28 | + if axis == 0: | |
29 | + for x in xrange(sx): | |
30 | + for y in xrange(sy): | |
31 | + max = image[0, y, x] | |
32 | + if max >= tmin and max <= tmax: | |
33 | + start = 1 | |
34 | + else: | |
35 | + start = 0 | |
36 | + for z in xrange(sz): | |
37 | + if image[z, y, x] > max: | |
38 | + max = image[z, y, x] | |
39 | + | |
40 | + elif image[z, y, x] < max and start: | |
41 | + break | |
42 | + | |
43 | + if image[z, y, x] >= tmin and image[z, y, x] <= tmax: | |
44 | + start = 1 | |
45 | + | |
46 | + out[y, x] = max | |
47 | + | |
48 | + #CORONAL | |
49 | + elif axis == 1: | |
50 | + for z in xrange(sz): | |
51 | + for x in xrange(sx): | |
52 | + max = image[z, 0, x] | |
53 | + if max >= tmin and max <= tmax: | |
54 | + start = 1 | |
55 | + else: | |
56 | + start = 0 | |
57 | + for y in xrange(sy): | |
58 | + if image[z, y, x] > max: | |
59 | + max = image[z, y, x] | |
60 | + | |
61 | + elif image[z, y, x] < max and start: | |
62 | + break | |
63 | + | |
64 | + if image[z, y, x] >= tmin and image[z, y, x] <= tmax: | |
65 | + start = 1 | |
66 | + | |
67 | + out[z, x] = max | |
68 | + | |
69 | + #CORONAL | |
70 | + elif axis == 2: | |
71 | + for z in xrange(sz): | |
72 | + for y in xrange(sy): | |
73 | + max = image[z, y, 0] | |
74 | + if max >= tmin and max <= tmax: | |
75 | + start = 1 | |
76 | + else: | |
77 | + start = 0 | |
78 | + for x in xrange(sx): | |
79 | + if image[z, y, x] > max: | |
80 | + max = image[z, y, x] | |
81 | + | |
82 | + elif image[z, y, x] < max and start: | |
83 | + break | |
84 | + | |
85 | + if image[z, y, x] >= tmin and image[z, y, x] <= tmax: | |
86 | + start = 1 | |
87 | + | |
88 | + out[z, y] = max | |
89 | + | |
90 | + | |
91 | +cdef DTYPE16_t get_colour(DTYPE16_t vl, DTYPE16_t wl, DTYPE16_t ww): | |
92 | + cdef DTYPE16_t out_colour | |
93 | + cdef DTYPE16_t min_value = wl - (ww / 2) | |
94 | + cdef DTYPE16_t max_value = wl + (ww / 2) | |
95 | + if vl < min_value: | |
96 | + out_colour = min_value | |
97 | + elif vl > max_value: | |
98 | + out_colour = max_value | |
99 | + else: | |
100 | + out_colour = vl | |
101 | + | |
102 | + return out_colour | |
103 | + | |
104 | +@cython.boundscheck(False) # turn of bounds-checking for entire function | |
105 | +@cython.cdivision(True) | |
106 | +cdef float get_opacity(DTYPE16_t vl, DTYPE16_t wl, DTYPE16_t ww) nogil: | |
107 | + cdef float out_opacity | |
108 | + cdef DTYPE16_t min_value = wl - (ww / 2) | |
109 | + cdef DTYPE16_t max_value = wl + (ww / 2) | |
110 | + if vl < min_value: | |
111 | + out_opacity = 0.0 | |
112 | + elif vl > max_value: | |
113 | + out_opacity = 1.0 | |
114 | + else: | |
115 | + out_opacity = 1.0/(max_value - min_value) * (vl - min_value) | |
116 | + | |
117 | + return out_opacity | |
118 | + | |
119 | +@cython.boundscheck(False) # turn of bounds-checking for entire function | |
120 | +@cython.cdivision(True) | |
121 | +cdef float get_opacity_f32(DTYPEF32_t vl, DTYPE16_t wl, DTYPE16_t ww) nogil: | |
122 | + cdef float out_opacity | |
123 | + cdef DTYPE16_t min_value = wl - (ww / 2) | |
124 | + cdef DTYPE16_t max_value = wl + (ww / 2) | |
125 | + if vl < min_value: | |
126 | + out_opacity = 0.0 | |
127 | + elif vl > max_value: | |
128 | + out_opacity = 1.0 | |
129 | + else: | |
130 | + out_opacity = 1.0/(max_value - min_value) * (vl - min_value) | |
131 | + | |
132 | + return out_opacity | |
133 | + | |
134 | + | |
135 | +@cython.boundscheck(False) # turn of bounds-checking for entire function | |
136 | +@cython.cdivision(True) | |
137 | +def mida(np.ndarray[DTYPE16_t, ndim=3] image, int axis, DTYPE16_t wl, | |
138 | + DTYPE16_t ww, np.ndarray[DTYPE16_t, ndim=2] out): | |
139 | + cdef int sz = image.shape[0] | |
140 | + cdef int sy = image.shape[1] | |
141 | + cdef int sx = image.shape[2] | |
142 | + | |
143 | + cdef DTYPE16_t min = image.min() | |
144 | + cdef DTYPE16_t max = image.max() | |
145 | + cdef DTYPE16_t vl | |
146 | + | |
147 | + cdef DTYPE16_t min_value = wl - (ww / 2) | |
148 | + cdef DTYPE16_t max_value = wl + (ww / 2) | |
149 | + | |
150 | + cdef float fmax=0.0 | |
151 | + cdef float fpi | |
152 | + cdef float dl | |
153 | + cdef float bt | |
154 | + | |
155 | + cdef float alpha | |
156 | + cdef float alpha_p = 0.0 | |
157 | + cdef float colour | |
158 | + cdef float colour_p = 0 | |
159 | + | |
160 | + cdef int x, y, z | |
161 | + | |
162 | + # AXIAL | |
163 | + if axis == 0: | |
164 | + for x in prange(sx, nogil=True): | |
165 | + for y in xrange(sy): | |
166 | + fmax = 0.0 | |
167 | + alpha_p = 0.0 | |
168 | + colour_p = 0.0 | |
169 | + for z in xrange(sz): | |
170 | + vl = image[z, y, x] | |
171 | + fpi = 1.0/(max - min) * (vl - min) | |
172 | + if fpi > fmax: | |
173 | + dl = fpi - fmax | |
174 | + fmax = fpi | |
175 | + else: | |
176 | + dl = 0.0 | |
177 | + | |
178 | + bt = 1.0 - dl | |
179 | + | |
180 | + colour = fpi | |
181 | + alpha = get_opacity(vl, wl, ww) | |
182 | + colour = (bt * colour_p) + (1 - bt * alpha_p) * colour * alpha | |
183 | + alpha = (bt * alpha_p) + (1 - bt * alpha_p) * alpha | |
184 | + | |
185 | + colour_p = colour | |
186 | + alpha_p = alpha | |
187 | + | |
188 | + if alpha >= 1.0: | |
189 | + break | |
190 | + | |
191 | + | |
192 | + #out[y, x] = <DTYPE16_t>((max_value - min_value) * colour + min_value) | |
193 | + out[y, x] = <DTYPE16_t>((max - min) * colour + min) | |
194 | + | |
195 | + | |
196 | + #CORONAL | |
197 | + elif axis == 1: | |
198 | + for z in prange(sz, nogil=True): | |
199 | + for x in xrange(sx): | |
200 | + fmax = 0.0 | |
201 | + alpha_p = 0.0 | |
202 | + colour_p = 0.0 | |
203 | + for y in xrange(sy): | |
204 | + vl = image[z, y, x] | |
205 | + fpi = 1.0/(max - min) * (vl - min) | |
206 | + if fpi > fmax: | |
207 | + dl = fpi - fmax | |
208 | + fmax = fpi | |
209 | + else: | |
210 | + dl = 0.0 | |
211 | + | |
212 | + bt = 1.0 - dl | |
213 | + | |
214 | + colour = fpi | |
215 | + alpha = get_opacity(vl, wl, ww) | |
216 | + colour = (bt * colour_p) + (1 - bt * alpha_p) * colour * alpha | |
217 | + alpha = (bt * alpha_p) + (1 - bt * alpha_p) * alpha | |
218 | + | |
219 | + colour_p = colour | |
220 | + alpha_p = alpha | |
221 | + | |
222 | + if alpha >= 1.0: | |
223 | + break | |
224 | + | |
225 | + out[z, x] = <DTYPE16_t>((max - min) * colour + min) | |
226 | + | |
227 | + #AXIAL | |
228 | + elif axis == 2: | |
229 | + for z in prange(sz, nogil=True): | |
230 | + for y in xrange(sy): | |
231 | + fmax = 0.0 | |
232 | + alpha_p = 0.0 | |
233 | + colour_p = 0.0 | |
234 | + for x in xrange(sx): | |
235 | + vl = image[z, y, x] | |
236 | + fpi = 1.0/(max - min) * (vl - min) | |
237 | + if fpi > fmax: | |
238 | + dl = fpi - fmax | |
239 | + fmax = fpi | |
240 | + else: | |
241 | + dl = 0.0 | |
242 | + | |
243 | + bt = 1.0 - dl | |
244 | + | |
245 | + colour = fpi | |
246 | + alpha = get_opacity(vl, wl, ww) | |
247 | + colour = (bt * colour_p) + (1 - bt * alpha_p) * colour * alpha | |
248 | + alpha = (bt * alpha_p) + (1 - bt * alpha_p) * alpha | |
249 | + | |
250 | + colour_p = colour | |
251 | + alpha_p = alpha | |
252 | + | |
253 | + if alpha >= 1.0: | |
254 | + break | |
255 | + | |
256 | + out[z, y] = <DTYPE16_t>((max - min) * colour + min) | |
257 | + | |
258 | + | |
259 | + | |
260 | +@cython.boundscheck(False) # turn of bounds-checking for entire function | |
261 | +@cython.cdivision(True) | |
262 | +cdef inline void finite_difference(DTYPE16_t[:, :, :] image, | |
263 | + int x, int y, int z, float h, float *g) nogil: | |
264 | + cdef int px, py, pz, fx, fy, fz | |
265 | + | |
266 | + cdef int sz = image.shape[0] | |
267 | + cdef int sy = image.shape[1] | |
268 | + cdef int sx = image.shape[2] | |
269 | + | |
270 | + cdef float gx, gy, gz | |
271 | + | |
272 | + if x == 0: | |
273 | + px = 0 | |
274 | + fx = 1 | |
275 | + elif x == sx - 1: | |
276 | + px = x - 1 | |
277 | + fx = x | |
278 | + else: | |
279 | + px = x - 1 | |
280 | + fx = x + 1 | |
281 | + | |
282 | + if y == 0: | |
283 | + py = 0 | |
284 | + fy = 1 | |
285 | + elif y == sy - 1: | |
286 | + py = y - 1 | |
287 | + fy = y | |
288 | + else: | |
289 | + py = y - 1 | |
290 | + fy = y + 1 | |
291 | + | |
292 | + if z == 0: | |
293 | + pz = 0 | |
294 | + fz = 1 | |
295 | + elif z == sz - 1: | |
296 | + pz = z - 1 | |
297 | + fz = z | |
298 | + else: | |
299 | + pz = z - 1 | |
300 | + fz = z + 1 | |
301 | + | |
302 | + gx = (image[z, y, fx] - image[z, y, px]) / (2*h) | |
303 | + gy = (image[z, fy, x] - image[z, py, x]) / (2*h) | |
304 | + gz = (image[fz, y, x] - image[pz, y, x]) / (2*h) | |
305 | + | |
306 | + g[0] = gx | |
307 | + g[1] = gy | |
308 | + g[2] = gz | |
309 | + | |
310 | + | |
311 | + | |
312 | +@cython.boundscheck(False) # turn of bounds-checking for entire function | |
313 | +@cython.cdivision(True) | |
314 | +cdef inline float calc_fcm_itensity(DTYPE16_t[:, :, :] image, | |
315 | + int x, int y, int z, float n, float* dir) nogil: | |
316 | + cdef float g[3] | |
317 | + finite_difference(image, x, y, z, 1.0, g) | |
318 | + cdef float gm = sqrt(g[0]*g[0] + g[1]*g[1] + g[2]*g[2]) | |
319 | + cdef float d = g[0]*dir[0] + g[1]*dir[1] + g[2]*dir[2] | |
320 | + cdef float sf = (1.0 - fabs(d/gm))**n | |
321 | + #alpha = get_opacity_f32(gm, wl, ww) | |
322 | + cdef float vl = gm * sf | |
323 | + return vl | |
324 | + | |
325 | +@cython.boundscheck(False) # turn of bounds-checking for entire function | |
326 | +@cython.cdivision(True) | |
327 | +def fast_countour_mip(np.ndarray[DTYPE16_t, ndim=3] image, | |
328 | + float n, | |
329 | + int axis, | |
330 | + DTYPE16_t wl, DTYPE16_t ww, | |
331 | + int tmip, | |
332 | + np.ndarray[DTYPE16_t, ndim=2] out): | |
333 | + cdef int sz = image.shape[0] | |
334 | + cdef int sy = image.shape[1] | |
335 | + cdef int sx = image.shape[2] | |
336 | + cdef float gm | |
337 | + cdef float alpha | |
338 | + cdef float sf | |
339 | + cdef float d | |
340 | + | |
341 | + cdef float* g | |
342 | + cdef float* dir = [ 0, 0, 0 ] | |
343 | + | |
344 | + cdef DTYPE16_t[:, :, :] vimage = image | |
345 | + cdef np.ndarray[DTYPE16_t, ndim=3] tmp = np.empty_like(image) | |
346 | + | |
347 | + cdef DTYPE16_t min = image.min() | |
348 | + cdef DTYPE16_t max = image.max() | |
349 | + cdef float fmin = <float>min | |
350 | + cdef float fmax = <float>max | |
351 | + cdef float vl | |
352 | + cdef DTYPE16_t V | |
353 | + | |
354 | + cdef int x, y, z | |
355 | + | |
356 | + if axis == 0: | |
357 | + dir[2] = 1.0 | |
358 | + elif axis == 1: | |
359 | + dir[1] = 1.0 | |
360 | + elif axis == 2: | |
361 | + dir[0] = 1.0 | |
362 | + | |
363 | + for z in prange(sz, nogil=True): | |
364 | + for y in range(sy): | |
365 | + for x in range(sx): | |
366 | + vl = calc_fcm_itensity(vimage, x, y, z, n, dir) | |
367 | + tmp[z, y, x] = <DTYPE16_t>vl | |
368 | + | |
369 | + cdef DTYPE16_t tmin = tmp.min() | |
370 | + cdef DTYPE16_t tmax = tmp.max() | |
371 | + | |
372 | + #tmp = ((max - min)/<float>(tmax - tmin)) * (tmp - tmin) + min | |
373 | + | |
374 | + if tmip == 0: | |
375 | + out[:] = tmp.max(axis) | |
376 | + elif tmip == 1: | |
377 | + lmip(tmp, axis, 700, 3033, out) | |
378 | + elif tmip == 2: | |
379 | + mida(tmp, axis, wl, ww, out) | ... | ... |
... | ... | @@ -0,0 +1,13 @@ |
1 | +from distutils.core import setup | |
2 | +from distutils.extension import Extension | |
3 | +from Cython.Distutils import build_ext | |
4 | + | |
5 | +import numpy | |
6 | + | |
7 | +setup( | |
8 | + cmdclass = {'build_ext': build_ext}, | |
9 | + ext_modules = [ Extension("invesalius/data/mips", ["invesalius/data/mips.pyx"], | |
10 | + include_dirs = [numpy.get_include()], | |
11 | + extra_compile_args=['-fopenmp'], | |
12 | + extra_link_args=['-fopenmp'],)] | |
13 | + ) | ... | ... |