Master Research Presentation

1. Master Research Presentation Automated Measurement of Brain Volumein Patients after aneurysmal Subarachnoid Hemorrhage Anne Kaspers source: socialmediaseo.net

2. Contents Introduction Methods Data Routine Evaluation Results Discussion Classification issues Strength and limitations Conclusion Questions

4. Methods

5. Data

6. Routine

7. Evaluation

8. Results

9. Discussion

10. Classification

11. Strength and limitations

12. Conclusion

13. Questionssource: thestrokefoundation.com source: socialmediaseo.net

15. Methods

16. Data

17. Routine

18. Evaluation

19. Results

20. Discussion

21. Classification

23. Conclusion

25. Methods

26. Data

27. Routine

28. Evaluation

29. Results

30. Discussion

31. Classification

33. Conclusion

35. Methods

36. Data

37. Routine

38. Evaluation

39. Results

40. Discussion

41. Classification

43. Conclusion

44. Questions1 Schaafsma JD et al. (2010) Intracranial aneurysms treated with coil placement: test characteristics of follow-up MR angiography--multicenter study. Radiology 1:209-218

46. Methods

47. Data

48. Routine

49. Evaluation

50. Results

51. Discussion

52. Classification

54. Conclusion

56. Methods

57. Data

58. Routine

59. Evaluation

60. Results

61. Discussion

62. Classification

64. Conclusion

65. QuestionsInput images T1 and T2 weighted image

67. Methods

68. Data

69. Routine

70. Evaluation

71. Results

72. Discussion

73. Classification

75. Conclusion

76. QuestionsRegistration Registered T1 weighted image and T2 weighted image

78. Methods

79. Data

80. Routine

81. Evaluation

82. Results

83. Discussion

84. Classification

86. Conclusion

87. QuestionsMask Creation Create mask to - include brain tissue - exclude skull and fatty tissue

89. Methods

90. Data

91. Routine

92. Evaluation

93. Results

94. Discussion

95. Classification

97. Conclusion

98. QuestionsPerform k-means Image of 10 clusters

100. Methods

101. Data

102. Routine

103. Evaluation

104. Results

105. Discussion

106. Classification

108. Conclusion

109. QuestionsCreate Mask Selection of clusters and mask

111. Methods

112. Data

113. Routine

114. Evaluation

115. Results

116. Discussion

117. Classification

119. Conclusion

120. QuestionsRemove Cerebellum Mask of the cerebrum on the T2 weigthed image

122. Methods

123. Data

124. Routine

125. Evaluation

126. Results

127. Discussion

128. Classification

130. Conclusion

131. QuestionsExtract Brain Images Extracted Brain in the T1 and T2 weighted image

133. Methods

134. Data

135. Routine

136. Evaluation

137. Results

138. Discussion

139. Classification

141. Conclusion

142. QuestionsShading Correction T2 weighted image with and without shading

144. Methods

145. Data

146. Routine

147. Evaluation

148. Results

149. Discussion

150. Classification

152. Conclusion

153. QuestionskNN Classification

155. Methods

156. Data

157. Routine

158. Evaluation

159. Results

160. Discussion

161. Classification

163. Conclusion

164. QuestionsNo partial volume effect

166. Introduction

167. Methods

168. Data

169. Routine

170. Evaluation

171. Results

172. Discussion

173. Classification

175. Conclusion

176. Questionsy y x z z x x T1 T2

178. Introduction

179. Methods

180. Data

181. Routine

182. Evaluation

183. Results

184. Discussion

185. Classification

187. Conclusion

188. Questions Sample of Structure 1 Sample of Structure 2 Intensity Location

190. Introduction

191. Methods

192. Data

193. Routine

194. Evaluation

195. Results

196. Discussion

197. Classification

199. Conclusion

200. Questions Sample of Structure 1 Sample of Structure 2 New Sample Intensity Location

202. Introduction

203. Methods

204. Data

205. Routine

206. Evaluation

207. Results

208. Discussion

209. Classification

211. Conclusion

212. Questions Sample of Structure 1 Sample of Structure 2 New Sample Intensity Location

214. Introduction

215. Methods

216. Data

217. Routine

218. Evaluation

219. Results

220. Discussion

221. Classification

223. Conclusion

224. Questionsk = 1 Sample of Structure 1 Sample of Structure 2 New Sample Intensity Location

226. Introduction

227. Methods

228. Data

229. Routine

230. Evaluation

231. Results

232. Discussion

233. Classification

235. Conclusion

238. Introduction

239. Methods

240. Data

241. Routine

242. Evaluation

243. Results

244. Discussion

245. Classification

247. Conclusion

250. Introduction

251. Methods

252. Data

253. Routine

254. Evaluation

255. Results

256. Discussion

257. Classification

259. Conclusion

262. Methods

263. Data

264. Routine

265. Evaluation

266. Results

267. Discussion

268. Classification

270. Conclusion

271. QuestionsRemove Edge for subcortical structures and cortical grey matter

273. Methods

274. Data

275. Routine

276. Evaluation

277. Results

278. Discussion

279. Classification

281. Conclusion

282. QuestionsMove back CSF from lateral ventricles Lateral ventricles before and after transfer CSF

284. Methods

285. Data

286. Routine

287. Evaluation

288. Results

289. Discussion

290. Classification

292. Conclusion

293. QuestionsRemove Infarcts

295. Methods

296. Data

297. Routine

298. Evaluation

299. Results

300. Discussion

301. Classification

303. Conclusion

304. QuestionsFinal result

306. Methods

307. Data

308. Routine

309. Evaluation

310. Results

311. Discussion

312. Classification

314. Conclusion

315. QuestionsT2 weighted image, Subcortical structures, Cortical grey matter, Peripheral CSF and Lateral ventricles

317. Methods

318. Data

319. Routine

320. Evaluation

321. Results

322. Discussion

323. Classification

325. Conclusion

326. QuestionsT2 weighted image, Subcortical structures, Cortical grey matter, Peripheral CSF and Lateral ventricles

328. Methods

329. Data

330. Routine

331. Evaluation

332. Results

333. Discussion

334. Classification

336. Conclusion

337. QuestionsObserver segmentations

339. Methods

340. Data

341. Routine

342. Evaluation

343. Results

344. Discussion

345. Classification

347. Conclusion

348. QuestionsObserver segmentations Routine segmentations

350. Methods

351. Data

352. Routine

353. Evaluation

354. Results

355. Discussion

356. Classification

358. Conclusion

360. Methods

361. Data

362. Routine

363. Evaluation

364. Results

365. Discussion

366. Classification

368. Conclusion

370. Introduction

371. Methods

372. Data

373. Routine

374. Evaluation

375. Results

376. Discussion

377. Classification

379. Conclusion

381. Methods

382. Data

383. Routine

384. Evaluation

385. Results

386. Discussion

387. Classification

389. Conclusion

391. Methods

392. Data

393. Routine

394. Evaluation

395. Results

396. Discussion

397. Classification

399. Conclusion

401. Methods

402. Data

403. Routine

404. Evaluation

405. Results

406. Discussion

407. Classification

409. Conclusion

411. Methods

412. Data

413. Routine

414. Evaluation

415. Results

416. Discussion

417. Classification

419. Conclusion

421. Methods

422. Data

423. Routine

424. Evaluation

425. Results

426. Discussion

427. Classification

429. Conclusion

431. Methods

432. Data

433. Routine

434. Evaluation

435. Results

436. Discussion

437. Classification

439. Conclusion

441. Methods

442. Data

443. Routine

444. Evaluation

445. Results

446. Discussion

447. Classification

449. Conclusion

451. Methods

452. Data

453. Routine

454. Evaluation

455. Results

456. Discussion

457. Classification

459. Conclusion

460. QuestionsNeurology Geert Jan Biessels Gabriël Rinkel Joanna Schaafsma Others Marja van Aken Ekke Kaspers Bart Waalewijn

462. Methods

463. Data

464. Routine

465. Evaluation

466. Results

467. Discussion

468. Classification

470. Conclusion

471. Questions

Master Research Presentation

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