Computer Aided Medical Procedures II (CAMP II) - IN2022
Lecture by Prof. Dr. Nassir Navab
Lecture Module IN2022
Informatics (Bachelor, Master), Informatics (Diploma: Praktische Informatik, Vertiefungsfach), Information Systems (Bachelor), Computational Science and Engineering (Master), TUM-BWL (Technikfach)
Attestation + Video Final Grades worth 40 points
Final Exam worth 60 points
- Date: July 31; Time: 8:30am-10:00am; Location: 5101.EG.501 (2501, Rudolf-Mößbauer-Hörsaal)
- 11 questions, one for each lecture
- Lectures: Wednesdays 12:30 - 14:00 MI 00.08.038 from 17.04.2013 to 17.07.2013 weekly
- Excercises: Thursdays 14:30 - 16:00 MI 03.13.008 from 18.04.2013 to 18.07.2013 weekly
- Note that on 3 Thursday's a lecture is offered instead of an exercise. The location will change to MI 03.13.010
This lecture teaches students to transfer their knowledge from the field of medical imaging and computer assisted interventions to practical algorithms. During the classes, the students get exposed to particular problems from segmentation, registration, navigation, tracking, and medical augmented reality and are then guided when implementing those algorithms themselves using MATLAB during the exercises.
The exercises take place in a lab room with MATLAB workstations.
- Basic knowledge in image computing (not necessarily acquired through the CAMP I lecture)
- Interest in algorithmic/implementation aspects
- Ability to work in small teams
- Specific knowledge in MATLAB is not required but beneficial. However, you should be somehow skilled in programming.
- Deep insight into medical image computing
- Ability to implement solutions for computer aided medical procedures
Video Presentation Topics
| Supervisor || Video Topic || Students |
| Diana Mateus || PCA (Taken) || Ralf Gutjahr |
| ICP (Taken) || Sabahattin Giritli |
Ole Tommy Vorren
Roberto Camacho Barranco
| Mehmet Yigitsoy || Mutual Information (Taken) || Jun Shen |
| Similarity Metrics in Registration (Taken) || Olga Khrutska |
| Maximilian Baust || Basic Level Sets || |
| Pascal Fallavollita || Tracking Solutions in Medicine (Taken) || Stavroula Timioteraki |
Faisal Ibne Mozher
| Optical vs. Video See Through HMD (Taken) || Priya Sarvachakan |
Sai Gokul Hariharan
| Patrick Wucherer & Philipp Stefan || Ray Casting (Taken) || Jihye Jang |
| Abouzar Eslami || TRE/FRE Error Evaluations (Taken) || Markus Muller |
| False Positive/False Negative/ROC || |
| Amin Katouzian || Gausssian Filtering (Taken) || Mark Muth |
| Loic Peter || Random Forests (Taken) || Amandeep Kaur |
| Tobias Lasser || SVD and Applications (Taken) || Xiao Huang |
| Rotations in Medical Imaging || |
| Christoph Hennersperger || Basic US Imaging (Taken) || Melanie Bernhardt |
- Image Processing / (Filtering, Morpholgical Operations, and Basic Segmentation Methods):
- Advanced Segmentation:
- Leo Grady, Yiyong Sun, James Williams. Three interactive graph-based segmentation methods applied to cardiovascular imaging. In Nikos Paragios, Yunmei Chen, Olivier Faugeras, editors. Handbook of mathematical models in computer vision. Springer, 2006.
- Yuri Boykov and Marie-Pierre Jolly. Interactive organ segmentation using graph cuts. In Scott L. Delp, Anthony M. DiGioia, and Branislav Jaramaz, editors, MICCAI, volume 1935 of Lecture Notes in Computer Science, pages 276--286. Springer, 2000.
- Y. Boykov and O. Veksler. Graph cuts in vision and graphis: theories and applications. In Nikos Paragios, Yunmei Chen, Olivier Faugeras, editors. Handbook of mathematical models in computer vision. Springer, 2006.
- Yuri Boykov, Gareth Funka-Lea. Graph Cuts and Efficient N-D Image Segmentation. In International Journal of Computer Vision (IJCV), vol. 70, no. 2, pp. 109-131, 2006.
- Leo Grady and Gareth Funka-Lea. Multi-label image segmentation for medical applications based on graph-theoretic electrical potentials. In Milan Sonka, Ioannis A. Kakadiaris, and Jan Kybic, editors, Computer Vision and Mathematical Methods in Medical and Biomedical Image Analysis, ECCV 2004 Workshops CVAMIA and MMBIA, number LNCS3117 in Lecture Notes in Computer Science, pages 230--245, Prague, Czech Republic, May 2004. Springer.
- Leo Grady and Eric Schwartz. Anisotropic interpolation on graphs: The combinatorial Dirichlet problem. Technical Report CAS/CNS-TR-03-014, Department of Cognitive and Neural Systems, Boston University, Boston, MA, July 2003.
- Web Page of Leo Grady a.k.a. everything you gotta know about random walker...
- [Hajnal2001] J. V. Hajnal, D. L. G. Hill, and D. J. Hawkes: Medical Image Registration. CRC Press, Biomedical Engineering Series, 2001
- Deformable Registration:
- [Modersitzki2004] Jan Modersitzki. Numerical methods for image registration. Oxford University Press, 2004.
- Christof Rezk-Salama, Klaus Engel, Markus Hadwiger, Joe M. Kniss and Daniel Weiskopf: Real Time Volume Graphics, Transatlantic Publishers, 2006
- Computer Aided Surgery:
- [CAS] Various Volumes of Computer Aided Surgery
- [CARS] Various Proceedings of CARS (Computer Assisted Radiology and Surgery - International Congress and Exhibition)
- [Grimson1999] W. Eric L. Grimson, Ron Kikinis, Ferenc A. Jolesz, and Peter McL. Black: Image-Guided Surgery. Scientific American, 280(6) pp. 62-69, 1999
- Computer Vision:
| TeachingForm |
| Title: || Computer Aided Medical Procedures II |
| Professor: || Prof. Dr. Nassir Navab |
| Tutors: || Pascal Fallavollita, Peter Maday, Mehmet Yigitsoy |
| Type: || Lecture |
| Information: || 2+2 SWS, 5 ECTS Credits (Module IN2022) |
| Term: || 2013SoSe |
| Abstract: || Computer science is playing an important, increasing role in medical practices. Medical imaging companies are no more asked by physicians to only produce images of anatomy. Instead, they are asked to design software and hardware systems to provide complex computer-aided solutions for diagnosis, intervention and therapy. There are more and more opportunities for computer science graduates to contribute to the development and deployment of medical solutions. Within the operating rooms, there is an increasing need for the integration and visualization of heterogeneous data acquired by numerous sensors. This course on computer aided medical procedures exposes the students to the challenges of building the operating rooms of the future. The main focus of the course is in imaging technologies especially intra-operative imaging as well as the visualization of this data. Techniques like segmentation and registration are explained in various classes. |