Computational anatomy | Wikipedia audio article
Channel: wikipedia tts
Date: 2019-01-21

This is an audio version of the Wikipedia Article:
https://en.wikipedia.org/wiki/Computational_anatomy


00:03:30 1 Genesis
00:05:59 2 History
00:14:19 3 The deformable template orbit model of computational anatomy
00:18:12 4 Shapes and forms
00:21:39 5 Groups and group actions
00:27:19 6 Lagrangian and Eulerian flows for generating diffeomorphisms
00:31:06 7 The diffeomorphism group of computational anatomy
00:33:57 7.1 The Sobolev smoothness condition on vector fields as modeled in a reproducing kernel Hilbert space
00:35:55 8 Diffeomorphometry: The metric space of shapes and forms
00:37:17 8.1 The right-invariant metric on diffeomorphisms
00:38:14 8.2 The metric on shapes and forms
00:39:51 9 The action integral for Hamilton's principle on diffeomorphic flows
00:40:42 10 Diffeomorphic or Eulerian shape momentum
00:47:24 11 The Euler–Lagrange equation on shape momentum for geodesics on the group of diffeomorphisms
00:48:23 11.1 Diffeomorphic shape momentum: a classical vector function
00:57:46 12 Riemannian exponential (geodesic positioning) and Riemannian logarithm (geodesic coordinates)
01:04:22 13 Hamiltonian formulation of computational anatomy
01:08:32 13.1 Stationarity of the Hamiltonian and kinetic energy along Euler–Lagrange
01:11:07 14 The metric on geodesic flows of landmarks, surfaces, and volumes within the orbit
01:12:42 15 Conservation laws on diffeomorphic shape momentum for computational anatomy
01:15:21 16 Geodesic interpolation of information between coordinate systems via variational problems
01:19:22 16.1 Matching based on minimizing kinetic energy action with endpoint condition
01:22:15 16.2 Matching based on geodesic shooting
01:23:47 17 Dense image matching in computational anatomy
01:28:56 17.1 LDDMM dense image matching
01:30:46 17.2 Hamiltonian LDDMM in the reduced advected state
01:38:53 17.3 Diffusion tensor image matching in computational anatomy
01:53:42 17.4 High Angular Resolution Diffusion Image (HARDI) matching in computational anatomy
01:57:28 18 Metamorphosis
02:00:21 19 Matching landmarks, curves, surfaces
02:06:13 19.1 Landmark or point matching with correspondence
02:11:41 19.2 Measure matching: unregistered landmarks
02:21:48 19.3 Curve matching
02:30:01 19.4 Surface matching
02:32:42 20 Growth and atrophy from longitudinal time-series
02:38:18 21 The random orbit model of computational anatomy
02:39:28 22 The Bayesian model of computational anatomy
02:42:49 23 Statistical shape theory in computational anatomy
02:43:50 24 Template estimation from populations
02:44:33 25 Software for diffeomorphic mapping
02:44:44 25.1 Cloud software



Listening is a more natural way of learning, when compared to reading. Written language only began at around 3200 BC, but spoken language has existed long ago.

Learning by listening is a great way to:
- increases imagination and understanding
- improves your listening skills
- improves your own spoken accent
- learn while on the move
- reduce eye strain

Now learn the vast amount of general knowledge available on Wikipedia through audio (audio article). You could even learn subconsciously by playing the audio while you are sleeping! If you are planning to listen a lot, you could try using a bone conduction headphone, or a standard speaker instead of an earphone.

Listen on Google Assistant through Extra Audio:
https://assistant.google.com/services/invoke/uid/0000001a130b3f91
Other Wikipedia audio articles at:
https://www.youtube.com/results?search_query=wikipedia+tts
Upload your own Wikipedia articles through:
https://github.com/nodef/wikipedia-tts
Speaking Rate: 0.8755022386338117
Voice name: en-US-Wavenet-B


"I cannot teach anybody anything, I can only make them think."
- Socrates


SUMMARY
=======
Computational anatomy is an interdisciplinary field of biology focused on quantitative investigation and modelling of anatomical shapes variability. It involves the development and application of mathematical, statistical and data-analytical methods for modelling and simulation of biological structures.
The field is broadly defined and includes foundations in anatomy, applied mathematics and pure mathematics, machine learning, computational mechanics, computational science, biological imaging, neuroscience, physics, probability, and statistics; it also has strong connections with fluid mechanics and geometric mechanics. Additionally, it complements newer, interdisciplinary fields like bioinformatics and neuroinformatics in the sense that its interpretation uses metadata derived from the original sensor imaging modalities (of which Magnetic Resonance Imaging is one example). It focuses on the anatomical structures being imaged, rather than the medical imaging devices. It is similar in spirit to the history of Computational linguistics, a discipline that focuses on the linguistic structures rather than the sensor acting as the transmission and communication medium(s).
In computational anatomy, the ...