SYSTEMS AND METHODS FOR PROCESSING IMAGES TO PREPARE SLIDES FOR PROCESSED IMAGES FOR DIGITAL PATHOLOGY
Systems and methods are disclosed for processing an electronic image corresponding to a specimen. One method for processing the electronic image includes: receiving a target electronic image of a slide corresponding to a target specimen, the target specimen including a tissue sample from a patient, applying a machine learning system to the target electronic image to determine deficiencies associated with the target specimen, the machine learning system having been generated by processing a plurality of training images to predict stain deficiencies and/or predict a needed recut, the training images including images of human tissue and/or images that are algorithmically generated; and based on the deficiencies associated with the target specimen, determining to automatically order an additional slide to be prepared.
1 . A method for processing an electronic image of a slide containing a specimen, the method comprising:
receiving a target electronic image of a slide corresponding to a target specimen, the specimen comprising a tissue sample from a patient;
applying a first machine learning model to the target electronic image to predict a presence of a feature correlating with a need for additional testing, wherein the first machine learning model is trained by processing a plurality of training images and training data associated with the training images to predict a likelihood that a new stain is desired for the slide;
generating, using a second machine learning model, a predicted likelihood that a new stain is desired for the slide based on the prediction generated by the first machine learning model; and
based on the prediction of the second machine learning model, determining to automatically order an additional slide to be prepared.
2 . The method of claim 1 , wherein determining to automatically order an additional slide to be prepared comprises determining that the predicted likelihood of the second machine learning model is greater than or equal to a predetermined amount, automatically ordering the additional slide to be prepared.
3 . The method of claim 1 , wherein automatically ordering the additional slide comprises ordering a new stain to be prepared for the slide corresponding to the target specimen.
4 . The method of claim 1 , wherein automatically ordering the additional slide comprises ordering a recut for the slide corresponding to the target specimen.
5 . The method of claim 1 , further comprising:
outputting an alert on a display indicating that the additional slide is being prepared.
6 . The method of claim 1 , wherein the feature correlating with a need for additional testing comprises a feature predictive of a cancer.
7 . The method of claim 6 , wherein the feature predictive of a cancer is a high-grade prostatic intraepithelial neoplasia (HGPIN) or an atypical small acinar proliferation (ASAP).
8 . A system for processing an electronic image corresponding to a specimen, the system comprising:
at least one memory storing instructions; and
at least one processor configured to execute the instructions to perform operations comprising:
receiving a target electronic image of a slide corresponding to a target specimen, the specimen comprising a tissue sample from a patient;
applying a first machine learning model to the target electronic image to predict a presence of a feature correlating with a need for additional testing, wherein the first machine learning model is trained by processing a plurality of training images and training data associated with the training images to predict a likelihood that a new stain is desired for the slide;
generating, using a second machine learning model, a predicted likelihood that a new stain is desired for the slide based on the prediction generated by the first machine learning model; and
based on the prediction of the second machine learning model, determining to automatically order an additional slide to be prepared.
9 . The system of claim 8 , wherein determining to automatically order an additional slide to be prepared comprises determining that the predicted likelihood of the second machine learning model is greater than or equal to a predetermined amount, automatically ordering the additional slide to be prepared.
10 . The system of claim 8 , wherein automatically ordering the additional slide comprises ordering a new stain to be prepared for the slide corresponding to the target specimen.
11 . The system of claim 8 , wherein automatically ordering the additional slide comprises ordering a recut for the slide corresponding to the target specimen.
12 . The system of claim 8 , further comprising:
outputting an alert on a display indicating that the additional slide is being prepared.
13 . The system of claim 8 , wherein the feature correlating with a need for additional testing comprises a feature predictive of a cancer.
14 . The system of claim 13 , wherein the feature predictive of a cancer is a high-grade prostatic intraepithelial neoplasia (HGPIN) or an atypical small acinar proliferation (ASAP).
15 . A non-transitory computer-readable medium storing instructions that, when executed by processor, cause the processor to perform a method for processing an electronic image corresponding to a specimen, the method comprising:
receiving a target electronic image of a slide corresponding to a target specimen, the specimen comprising a tissue sample from a patient;
applying a first machine learning model to the target electronic image to predict a presence of a feature correlating with a need for additional testing, wherein the first machine learning model is trained by processing a plurality of training images and training data associated with the training images to predict a likelihood that a new stain is desired for the slide;
generating, using a second machine learning model, a predicted likelihood that a new stain is desired for the slide based on the prediction generated by the first machine learning model; and
based on the prediction of the second machine learning model, determining to automatically order an additional slide to be prepared.
16 . The non-transitory computer-readable medium of claim 15 , wherein determining to automatically order an additional slide to be prepared comprises determining that the predicted likelihood of the second machine learning model is greater than or equal to a predetermined amount, automatically ordering the additional slide to be prepared.
17 . The non-transitory computer-readable medium of claim 15 , wherein automatically ordering the additional slide comprises ordering a new stain to be prepared for the slide corresponding to the target specimen or ordering a recut for the slide corresponding to the target specimen.
18 . The non-transitory computer-readable medium of claim 15 , further comprising:
outputting an alert on a display indicating that the additional slide is being prepared.
19 . The non-transitory computer-readable medium of claim 15 , wherein the feature correlating with a need for additional testing comprises a feature predictive of a cancer.
20 . The non-transitory computer-readable medium of claim 19 , wherein the feature predictive of a cancer is a high-grade prostatic intraepithelial neoplasia (HGPIN) or an atypical small acinar proliferation (ASAP).