Image analysis for animal health assessments
The present teachings generally include techniques for characterizing the health of an animal (e.g., gastrointestinal health) using image analysis (e.g., of a sample of an exudate such as mucus) as a complement, alternative, or a replacement to traditional laboratory analyses of biological specimens. The present teachings may further include techniques for personalizing a health and wellness plan (including, but not limited to, a dietary supplement such as a customized formula based on a health assessment), where such a plan may be based on one or more of the health characterization techniques described herein. The present teachings may also or instead include techniques or plans for continuous care for an animal, e.g., by executing health characterization and heath planning techniques in a cyclical fashion. A personalized supplement system (e.g., using a personalized supplement, personalized dosing device, and personalized packaging) may also or instead be created using the present teachings.
1. A method of analyzing a stool sample image to provide a health assessment of an animal, the method comprising:
receiving an image of a stool sample from a camera of a smartphone, wherein the image is a non-microscopic image of the stool sample;
identifying and extracting a region of interest within the image for further analysis;
analyzing one or more of a geometric attribute, a texture attribute, and a color attribute in the region of interest to identify one or more features of the stool sample, the one or more features of the stool sample including a presence of a non-stool substance;
applying a model to the one or more features of the stool sample including the non-stool substance, the model created by identifying a number of associations between one or more image-based features of stool and one or more health characteristics related thereto; and
using the model, and without laboratory analysis of the stool sample, predicting a health characteristic of an animal that deposited the stool sample, the health characteristic including a determination related to a presence or absence of a parasite.
2. The method of claim 1 , wherein the non-stool substance includes a foreign object.
3. The method of claim 2 , wherein the foreign object includes the parasite.
4. The method of claim 1 , further comprising providing a recommendation based on the health characteristic.
5. The method of claim 4 , wherein the recommendation includes a customized health plan for the animal that deposited the stool sample.
6. The method of claim 4 , wherein the recommendation includes one or more of a food, a supplement, and a medicine.
7. The method of claim 1 , further comprising analyzing the health characteristic in view of a reference database to determine a treatment for the animal that deposited the stool sample.
8. The method of claim 7 , wherein the reference database includes a historical database including data from analyses of a plurality of biological samples.
9. The method of claim 1 , wherein the image includes a digital photograph.
10. The method of claim 1 , wherein the one or more features relate to the geometric attribute, the color attribute, and the texture attribute of the stool sample, and wherein the geometric attribute includes one or more of a geometric property and a derived attribute related to geometry, the color attribute includes one or more of a color and a derived attribute related to the color, and the texture attribute includes one or more of a texture property and a derived attribute related to texture.
11. The method of claim 1 , wherein the one or more features are identified using a convolutional neural network (CNN) model.
12. The method of claim 1 , further comprising providing a report for the animal that includes the health characteristic.
13. The method of claim 1 , further comprising receiving metadata associated with the image, the metadata including a questionnaire response related to one or more of a health, a behavior, a current diet, a supplement, a medication, ethnographic information, a breed, a weight of the animal, a weight of the stool sample, and a size of the animal, and wherein the metadata is used at least in part in predicting the health characteristic.
14. A computer program product for analyzing a stool sample image to provide a health assessment of an animal, the computer program product comprising computer executable code embodied in a non-transitory computer readable medium that, when executing on one or more computing devices, performs the steps of:
receiving an image of a stool sample from a camera of a smartphone, wherein the image is a non-microscopic image of the stool sample;
identifying and extracting a region of interest within the image for further analysis;
analyzing one or more of a geometric attribute, a texture attribute, and a color attribute in the region of interest to identify one or more features of the stool sample, the one or more features of the stool sample including a presence of a non-stool substance;
applying a model to the one or more features of the stool sample including the non-stool substance, the model created by identifying a number of associations between one or more image-based features of stool and one or more health characteristics related thereto; and
using the model, and without laboratory analysis of the stool sample, predicting a health characteristic of an animal that deposited the stool sample, the health characteristic including a determination related to a presence or absence of a parasite.
15. The computer program product of claim 14 , wherein the non-stool substance includes a foreign object.
16. The computer program product of claim 15 , wherein the foreign object includes the parasite.
17. A system for analyzing a biological image to provide a health assessment of an animal, the system comprising:
a data network;
a smartphone coupled to the data network; and
a remote computing resource coupled to the data network and accessible to the smartphone through the data network, the remote computing resource including a processor and a memory, the memory storing code executable by the processor to perform the steps of:
receiving an image taken from a camera of the smartphone over the data network, the image including a biological sample, wherein the image is a non-microscopic image of the biological sample;
identifying and extracting a region of interest within the image for further analysis;
analyzing one or more of a geometric attribute, a texture attribute, and a color attribute in the region of interest to identify one or more features of the biological sample, the one or more features of the biological sample including a presence of a foreign object;
applying a model to the one or more features of the biological sample including the foreign object, the model created by identifying a number of associations between one or more image-based features of biological samples and one or more health characteristics related thereto;
using the model, predicting a health characteristic of an animal from which the biological sample originated without laboratory analysis of the biological sample, the health characteristic including a determination related to a presence or absence of a parasite; and
presenting the health characteristic on the smartphone.
18. The system of claim 17 , wherein the foreign object includes the parasite.