# US 12,602,787 B2 · Procedure for control, prognosis and comparative support related to dermatological lesions

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- Number: US 12,602,787 B2
- Document ID: US12602787B2
- Status: Granted
- Kind: B2
- Application number: 18/370,559
- Filed: 2023-09-20
- Published: 2024-06-27
- Granted: 2026-04-14
- Earliest claimed: 2022-12-21
- Assignees: Skilled Skin Sl
- Applicants: Skilled Skin Sl
- Inventors: Alberto Siré Langa; David Reifs Jiménez; Ibon Uribe Elorrieta
- Web page: https://patentgrep.com/patent/US12602787B2

## CPC

- G06T 7/0012: {Biomedical image inspection}
- G06T 7/0014: {using an image reference approach}
- A61B 5/1032: {Determining colour of tissue for diagnostic purposes}
- A61B 5/445: {Evaluating skin irritation or skin trauma, e.g. rash, eczema, wound, bed sore}
- G06T 7/11: Region-based segmentation
- G06T 7/62: of area, perimeter, diameter or volume
- G06T 11/10: Texturing; Colouring; Generation of textures or colours (retouching, inpainting or scratch removal G06T5/77)
- G06T 11/26: Drawing of charts or graphs
- G06V 10/25: Determination of region of interest [ROI] or a volume of interest [VOI]
- G06V 10/764: using classification, e.g. of video objects
- G06V 10/82: using neural networks
- G16H 30/20: for handling medical images, e.g. DICOM, HL7 or PACS
- G16H 30/40: for processing medical images, e.g. editing
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- G16H 50/30: for calculating health indices; for individual health risk assessment
- G16H 50/70: for mining of medical data, e.g. analysing previous cases of other patients
- G06T 2207/20084: Artificial neural networks [ANN]
- G06T 2207/30088: Skin; Dermal
- G06T 2207/30096: Tumor; Lesion
- G06V 2201/03: Recognition of patterns in medical or anatomical images
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

An ulcer-related control, prognosis and comparative support procedure is provided that includes the following stages: measuring the area of the ulcer and ROI (1) by taking an image of the area of the ulcer and ROI (1.a), segmenting the tissues obtained in the image of the ulcer area and ROI (1.a)., obtaining the base characteristics vector, depicting the state of the tissues, classifying ulcers, supporting user's decisions, archiving registered clinical cases, and supporting user's decisions by comparing the global characteristics vector with the global characteristics vectors of the registered ulcer clinical cases.

## Claims

### Claim 1

An ulcer-related control, prognosis and comparative support procedure comprising:
measuring an area of an ulcer and ROI by taking an image of the area of the ulcer and ROI;
segmenting tissues obtained in the image of the ulcer area and ROI;
obtaining a base characteristics vector;
depicting a state of the tissues;
classifying the ulcer;
supporting a user's decisions;
archiving registered clinical cases,
wherein the user's decisions are supported by comparing a global characteristics vector related to the ulcer with a global characteristics vectors of registered ulcer clinical cases;
wherein the global characteristics vector is obtained by obtaining the base characteristics vector of the segmentation of the tissues of the image of the area of the ulcer and ROI and adding patient data vector, wherein the patient data vector is obtained from patient-related characteristics, clinical data of the patient and patient risk scale;
wherein the global characteristics vector is compared with the global characteristics vectors of registered ulcer clinical cases to obtain a closest registered clinical case with characteristics closest to those of the ulcer-related analyzed clinical case, wherein the closest registered clinical case has the lowest Euclidean distance; and
wherein the measurement of the area of the ulcer and ROI by taking images is carried out with the image taken of the area of the ulcer and the region of interest (ROI) processed by an API using distance in cm between two points on the image as a reference for determining the area of the ulcer and ROI in cm2.

### Claim 2 (depends on 1)

The ulcer-related control, prognosis and comparative support procedure according to claim 1, wherein the segmentation of the tissues obtained in the image of the area of the ulcer and ROI and the obtaining of the base characteristics vector is performed using the pretrained CNNs (Convolutional Neural Networks), which classify tissues as granulated, sloughed, necrotic, and hyper-granulated.

### Claim 3 (depends on 1)

The ulcer-related control, prognosis and comparative support procedure according to claim 1, wherein the representation of the tissues reconstructs the image based on the base characteristics vector representing each type of tissue with a specific color.

### Claim 4 (depends on 1)

The ulcer-related control, prognosis and comparative support procedure according to claim 1, wherein the global characteristics vector of the ulcer clinical case is archived in a safe environment.