Spectral-guided wound modeling and therapeutic dressing

A system for multispectral wound tissue classification and customized dressing fabrication, comprising:

• a. an imaging apparatus comprising:
• i. a plurality of wavelength-specific optical emitters configured to illuminate a wound;
• ii. at least one image sensor spatially aligned with the optical emitters to capture multispectral images;
• iii. a depth sensor providing three-dimensional spatial data of the wound;
• b. a processing unit comprising at least one processor and non-transitory computer-readable memory storing instructions configured to cause the at least one processor to:
• i. process multispectral image data and depth data;
• ii. classify wound tissue types using stored machine-learning algorithms to generate a wound tissue classification map;
• iii. generate a three-dimensional wound surface model;
• iv. create a digital fabrication file defining a customized dressing matching the wound surface and tissue classifications, including heterogeneous therapeutic regions selected based on the classified tissue types, wherein the customized dressing varies in at least one physical or chemical property comprising a spatial distribution of therapeutic compound identity and/or therapeutic compound concentration across multiple heterogeneous regions of a single fabricated dressing, and wherein the digital fabrication file encodes region-wise material deposition instructions and/or therapeutic compound dosing instructions comprising at least one of multi-material toolpaths or multi-dosing toolpaths aligned to the wound tissue classification map, and wherein the digital fabrication file further encodes (i) cutting instructions for cutting at least one sheet material layer of the customized dressing and (ii) fiducial-based registration data mapping the wound tissue classification map to a printer coordinate system;
• and
• c. a computer-controlled three-dimensional printer configured to fabricate the customized dressing based on the digital fabrication file, wherein the three-dimensional printer comprises a hybrid fabrication unit including (i) a cutting module configured to execute the cutting instructions to cut the at least one sheet material layer and (ii) a multi-material deposition module configured to deposit the heterogeneous therapeutic regions onto the at least one sheet material layer by executing the region-wise material deposition instructions and/or therapeutic compound dosing instructions, and wherein the hybrid fabrication unit includes an assembly pallet with fiducial markers detectable by a vision system to align the multi-material deposition module using the fiducial-based registration data.

A non-transitory computer-readable medium storing instructions executable by a processor, configured to cause a system to perform a method comprising:

• a. receiving multispectral image data captured from a wound illuminated at multiple predetermined optical wavelengths;
• b. classifying tissue types within the wound using trained machine-learning models based on reflectance characteristics, thereby generating a wound tissue classification map that delineates spatial regions of different tissue types in the wound;
• c. generating a three-dimensional model of the wound surface from depth sensor data;
• d. automatically designing a digital fabrication file for a customized wound dressing based on the tissue classifications and the three-dimensional model, wherein the customized wound dressing includes heterogeneous regions having therapeutic compounds specifically aligned with the classified tissue types, the heterogeneous regions providing a spatial distribution of therapeutic compound identity and/or therapeutic compound concentration across multiple heterogeneous regions of a single fabricated dressing, and wherein the digital fabrication file encodes region-wise material deposition instructions and/or therapeutic compound dosing instructions comprising at least one of multi-material toolpaths or multi-dosing toolpaths aligned to the wound tissue classification map, and wherein the digital fabrication file further encodes (i) cutting instructions for cutting at least one sheet material layer of the customized wound dressing and (ii) fiducial-based registration data mapping the wound tissue classification map to a printer coordinate system;
• and
• e. transmitting the digital fabrication file to a three-dimensional printer to fabricate a tangible customized therapeutic wound dressing, wherein the three-dimensional printer comprises a hybrid fabrication unit including (i) a cutting module configured to execute the cutting instructions to cut the at least one sheet material layer and (ii) a multi-material deposition module configured to deposit the heterogeneous regions onto the at least one sheet material layer by executing the region-wise material deposition instructions and/or therapeutic compound dosing instructions, and wherein the hybrid fabrication unit includes an assembly pallet with fiducial markers detectable by a vision system to align the multi-material deposition module using the fiducial-based registration data.

A system for multispectral wound tissue classification and time-sequenced customized dressing fabrication, comprising:

• a. an imaging apparatus comprising:
• i. a plurality of distinct wavelength-specific optical emitters configured to illuminate a wound;
• ii. at least one image sensor spatially aligned with the optical emitters to capture multispectral images of the wound;
• iii. a depth sensor calibrated with the image sensor to provide three-dimensional spatial data of the wound;
• b. a processing unit comprising at least one processor and a non-transitory computer-readable memory storing instructions configured to cause the at least one processor to:
• i. preprocess the multispectral image data and depth data captured from the wound by at least one of calibration, reflectance normalization, spatial registration, noise filtering, or artifact correction to generate preprocessed data;
• ii. classify wound tissue types by applying a trained machine-learning algorithm to the preprocessed data, thereby generating a wound tissue classification map that delineates spatial regions of different tissue types in the wound;
• iii. generate a three-dimensional digital surface model of the wound from the depth data, the model representing the wound's topography and dimensions;
• iv. create a first digital fabrication file defining a patient-specific customized three-dimensional wound dressing corresponding to a current state of the wound, the first digital fabrication file specifying a geometry conforming to the wound's surface and including heterogeneous regions with physical or chemical properties selected based on the classified tissue types at corresponding locations, wherein the physical or chemical properties comprise a spatial distribution of therapeutic compound identity and/or therapeutic compound concentration across multiple heterogeneous regions of a single fabricated dressing, and wherein the first digital fabrication file encodes region-wise material deposition instructions and/or therapeutic compound dosing instructions comprising at least one of multi-material toolpaths or multi-dosing toolpaths aligned to the wound tissue classification map, and wherein the first digital fabrication file further encodes (i) cutting instructions for cutting at least one sheet material layer of the patient-specific customized three-dimensional wound dressing and (ii) fiducial-based registration data mapping the wound tissue classification map to a printer coordinate system;
• v. predict a wound healing progression using a multi-stage predictive wound model based on the wound tissue classification map and the three-dimensional digital surface model, thereby determining at least one anticipated future wound state comprising a predicted distribution of tissue types and wound geometry at a future time;
• and
• vi. create at least one additional digital fabrication file defining at least one future-stage custom wound dressing for the anticipated future wound state, the at least one future-stage custom wound dressing having a geometry and material composition modified according to the predicted changes in the wound, wherein the at least one additional digital fabrication file encodes region-wise material deposition instructions and/or therapeutic compound dosing instructions comprising at least one of multi-material toolpaths or multi-dosing toolpaths aligned to the predicted distribution of tissue types for the anticipated future wound state, and wherein the at least one additional digital fabrication file further encodes (i) cutting instructions for cutting at least one sheet material layer of the at least one future-stage custom wound dressing and (ii) fiducial-based registration data mapping the predicted distribution of tissue types to the printer coordinate system;
• and
• c. a computer-controlled three-dimensional printer configured to fabricate the patient-specific customized three-dimensional wound dressing and the at least one future-stage custom wound dressing based on the respective digital fabrication files, wherein the three-dimensional printer comprises a hybrid fabrication unit including (i) a cutting module configured to execute respective cutting instructions to cut at least one respective sheet material layer for each of the patient-specific customized three-dimensional wound dressing and the at least one future-stage custom wound dressing and (ii) a multi-material deposition module configured to deposit the heterogeneous regions onto the respective sheet material layers by executing respective region-wise material deposition instructions and/or therapeutic compound dosing instructions, and wherein the hybrid fabrication unit includes an assembly pallet with fiducial markers detectable by a vision system to align the multi-material deposition module using respective fiducial-based registration data.