Hybrid convolutional wavelet networks for predicting treatment response via radiological images of bowel disease
US12400327B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 16, 2023 |
| Grant date | Aug 26, 2025 |
| Priority date | — |
| Expiry date | Mar 6, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30096
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
In some embodiments, the present disclosure relates to a non-transitory computer-readable medium storing computer-executable instructions that, when executed, cause a processor to perform operations, including forming an imaging dataset having imaging data corresponding to one or more radiological images of a patient having a bowel disease; operating upon the imaging data with one or more convolutional neural network (CNN) segments configured to generate a plurality of CNN outputs, the one or more CNN segments respectively including a convolution layer configured to perform a convolution on the imaging data; and applying a wavelet network to the plurality of CNN outputs to generate a plurality of convolution wavelet network (CWN) outputs, the wavelet network being configured to decompose the plurality of CNN outputs according to a mother wavelet. A predictive signature associated with disease response or risk is constructed using the plurality of CWN outputs.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.