View source for 18373494. MECHANISMS FOR BRAIN ANALYSIS simplified abstract (KONINKLIJKE PHILIPS N.V.)

=MECHANISMS FOR BRAIN ANALYSIS=


==Organization Name==

[[:Category:KONINKLIJKE PHILIPS N.V.|KONINKLIJKE PHILIPS N.V.]]


[[Category:KONINKLIJKE PHILIPS N.V.]]

==Inventor(s)==

[[:Category:Evan Schwab of Cambridge MA (US)|Evan Schwab of Cambridge MA (US)]][[Category:Evan Schwab of Cambridge MA (US)]]

==MECHANISMS FOR BRAIN ANALYSIS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18373494 titled 'MECHANISMS FOR BRAIN ANALYSIS

==Simplified Explanation==

The method described in the patent application involves using diffusion magnetic resonance imaging to localize structural connectivity biomarkers in neurological diseases. Here is a simplified explanation of the abstract:

* Dividing brain volume into connected brain regions
* Extracting voxels along fiber connections between brain regions
* Applying a deep neural network to imaging features from the voxels
* Outputting disease classification based on neural network
* Using multi-instance learning to predict healthy or diseased brain based on fiber connections

### Potential Applications
This technology could be used in the early detection and monitoring of neurological diseases such as Alzheimer's, Parkinson's, and multiple sclerosis.

### Problems Solved
This technology helps in identifying structural connectivity biomarkers in neurological diseases, which can aid in early diagnosis and personalized treatment plans.

### Benefits
- Early detection of neurological diseases
- Personalized treatment plans
- Monitoring disease progression

### Potential Commercial Applications
This technology could be valuable for healthcare providers, research institutions, and pharmaceutical companies developing treatments for neurological diseases.

### Possible Prior Art
One possible prior art could be the use of diffusion MRI in studying brain connectivity in neurological diseases. However, the specific method outlined in this patent application may be novel in its approach to localizing structural connectivity biomarkers.

#### Unanswered Questions

### How does this technology compare to existing methods for identifying biomarkers in neurological diseases?
This article does not provide a direct comparison to existing methods, leaving the reader to wonder about the advantages and limitations of this new approach.

### What are the potential limitations or challenges in implementing this technology in clinical settings?
The article does not address the practical aspects of implementing this technology in real-world clinical settings, leaving questions about scalability, cost-effectiveness, and regulatory considerations.


==Original Abstract Submitted==

A method for localizing structural connectivity biomarkers in neurological diseases, includes dividing a diffusion magnetic resonance imaging brain volume into a set of connected brain regions; extracting three-dimensional voxels along fiber connections which structurally connect the connected brain regions, wherein the brain regions comprise bundles of neurons; applying a deep neural network to diffusion magnetic resonance imaging features extracted from the three-dimensional voxels for each set of fiber connections which structurally connect brain regions; outputting a disease classification based on applying the deep neural network; and applying multi-instance learning to predict whether each fiber connection is indicative of a healthy brain or a diseased brain.



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