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EP-4740215-A1 - GRAPHICAL USER INTERFACE FOR PRESCREENED IN-VIVO STUDIES

EP4740215A1EP 4740215 A1EP4740215 A1EP 4740215A1EP-4740215-A1

Abstract

A system for presenting prescreened in-vivo studies includes at least one processor and at least one memory storing instructions. The instructions, when executed by the processor(s), cause the system at least to: access prescreened in-vivo studies of at least a portion of gastrointestinal tracts (GIT) of patients, where each of the prescreened in-vivo studies includes respective in-vivo images; access, for each of the prescreened in-vivo studies, respective prescreening information generated prior to the respective in-vivo images being read by a healthcare professional, where the respective prescreening information includes information on whether one or more GIT conditions were indicated by image prescreening processing of the respective in-vivo images; and provide a graphical user interface configured to present a listing for each of the prescreened in-vivo studies, where the graphical user interface is configured to present, in each listing, one or more graphical indications corresponding to whether the GIT condition(s) were indicated.

Inventors

  • SOHLDEN, Ryan, S.
  • QUEALY, Lisa, M.

Assignees

  • Covidien LP

Dates

Publication Date
20260513
Application Date
20240618

Claims (15)

  1. 1. A system for presenting prescreened in-vivo studies, the system comprising: at least one processor; and at least one memory storing instructions which, when executed by the at least one processor, cause the system at least to: access a plurality of prescreened in-vivo studies of at least a portion of gastrointestinal tracts (GIT) of patients, each of the plurality of prescreened in-vivo studies comprising respective in-vivo images; access, for each of the plurality of prescreened in-vivo studies, respective prescreening information generated prior to the respective in-vivo images being read by a healthcare professional, the respective prescreening information comprising information on whether one or more GIT conditions were indicated by image prescreening processing of the respective in-vivo images; and provide a graphical user interface configured to present a listing for each of the plurality of prescreened in-vivo studies, the graphical user interface configured to present, in each listing, one or more graphical indications corresponding to whether the one or more GIT conditions were indicated by the image prescreening processing.
  2. 2. The system of claim 1, wherein, for each of the plurality of prescreened in-vivo studies, the image prescreening processing processes the respective in-vivo images prior to any healthcare professional reading the respective in-vivo images.
  3. 3. The system of claim 1 or claim 2, wherein the image prescreening processing is performed by at least one machine learning model.
  4. 4. The system of any one of claims 1-3, wherein the one or more GIT conditions comprise bleeding, vascular disease, and inflammatory disease, and wherein the one or more graphical indications comprise a graphical indication that bleeding was indicated, a graphical indication that vascular disease was indicated, and a graphical indication that inflammatory disease was indicated.
  5. 5. The system of any one of claims 1-4, wherein the image prescreening processing is performed by at least a convolutional neural network configured to detect the one or more GIT conditions in in-vivo images.
  6. 6. The system of any one of claims 1-5, wherein the instructions, when executed by the at least one processor, further cause the system at least to: prioritize display of listings which have one or more graphical indications indicating that one or more GIT conditions were indicated; and display the listings that are prioritized for display before displaying listings that are not prioritized for display.
  7. 7. The system of any one of claims 1-6, wherein the graphical user interface further comprises control elements configured to sort the listings according to one of the one or more graphical indications selected by a user of the graphical user interface.
  8. 8. A method for presenting in-vivo studies, the method comprising: accessing a plurality of prescreened in-vivo studies of at least a portion of gastrointestinal tracts (GIT) of patients, each of the plurality of prescreened in-vivo studies comprising respective in-vivo images; accessing, for each of the plurality of prescreened in-vivo studies, respective prescreening information generated prior to the respective in-vivo images being read by a healthcare professional, the respective prescreening information comprising information on whether one or more GIT conditions were indicated by image prescreening processing of the respective in-vivo images; and providing a graphical user interface configured to present a listing for each of the plurality of prescreened in-vivo studies, the graphical user interface configured to present, in each listing, one or more graphical indications corresponding to whether the one or more GIT conditions were indicated by the image prescreening processing.
  9. 9. The method of claim 8, wherein, for each of the plurality of prescreened in-vivo studies, the image prescreening processing processes the respective in-vivo images prior to any healthcare professional reading the respective in-vivo images.
  10. 10. The method of claim 8 or claim 9, wherein the image prescreening processing is performed by at least one machine learning model.
  11. 11. The method of any one of claims 8-10, wherein the one or more GIT conditions comprise bleeding, vascular disease, and inflammatory disease, and wherein the one or more graphical indications comprise a graphical indication that bleeding was indicated, a graphical indication that vascular disease was indicated, and a graphical indication that inflammatory disease was indicated.
  12. 12. The method of any one of claims 8-11, wherein the image prescreening processing is performed by at least a convolutional neural network configured to detect the one or more GIT conditions in in-vivo images.
  13. 13. The method of any one of claims 8-12, further comprising: prioritizing display of listings which have one or more graphical indications indicating that one or more GIT conditions were indicated; and displaying the listings that are prioritized for display before displaying listings that are not prioritized for display.
  14. 14. The method of any one of claims 8-13, wherein the graphical user interface further comprises control elements configured to sort the listings according to one of the one or more graphical indications selected by a user of the graphical user interface.
  15. 15. A processor-readable medium storing instructions which, when executed by at least one processor of a system, cause the system at least to perform the method of any one of claims 8-14.

Description

GRAPHICAL USER INTERFACE FOR PRESCREENED IN-VIVO STUDIES CROSS-REFERENCE TO RELATED APPLICATIONS [0001] The present application claims the benefit of and priority to U.S. Provisional Application No. 63/525,457, filed July 7, 2023, which is hereby incorporated by reference herein in its entirety. TECHNICAL FIELD [0002] The present disclosure relates to in-vivo studies and, more particularly, to graphical user interfaces for presenting prescreened in-vivo studies. BACKGROUND [0003] Capsule endoscopy (CE) allows examining of a gastrointestinal tract (GIT) endoscopically. There are capsule endoscopy systems and methods that are aimed at examining a specific portion of the GIT, such as the small bowel (SB) or the colon. CE is a non-invasive procedure which does not require the patient to be admitted to a hospital, and the patient can continue most daily activities while the capsule is in his body. [0004] For a typical CE procedure, the patient is referred to a procedure by a physician. The patient then arrives at a medical facility (e.g., a clinic or a hospital), to perform the procedure. The capsule, which is about the size of a multi-vitamin, is swallowed by the patient under the supervision of a healthcare professional (e.g., a nurse or a physician) at the medical facility and the patient is provided with a wearable device (e.g., a belt having a recorder in a pouch and a strap to be placed around the patient’s shoulder). The wearable device typically includes a storage device. The patient may be given guidance and/or instructions and then is released to his or her daily activities. [0005] The capsule captures images as it travels naturally through the GIT. Images and additional data (e.g., metadata) are then transmitted to the recorder that is worn by the patient. The capsule is typically disposable and passes naturally with a bowel movement. The procedure data (e.g., the captured images or a portion of them and additional metadata) is stored in the storage device of the wearable device. [0006] The procedure data is uploaded from the wearable device to a computing system, which has a software engine stored thereon. The procedure data is then processed by the software engine to generate a compiled study. Typically, the number of images in the procedure data to be processed is of the order of tens of thousands, and the generated study typically includes thousands of images. [0007] A reader (which may be the procedure supervising physician, a dedicated physician, or the referring physician) may access the study via a reader application. The reader then reviews the study, evaluates the procedure, and provides input via the reader application. Since the reader needs to review thousands of images, the reading time of a study may usually take between half an hour to an hour on average and the reading task may be tiresome. A report is then generated by the reader application based on the compiled study and the reader’s input. On average, it may take an hour to generate a report. The report may include, for example, images of interest (e.g., images which are identified as including pathologies) selected by the reader; evaluation or diagnosis of the patient’s medical condition based on the procedure’s data (i.e., the study), and/or recommendations for follow up and/or treatment provided by the reader. The report may then be forwarded to a referring physician. The referring physician may decide on a required follow up or treatment based on the report. SUMMARY [0008] The present disclosure relates to graphical user interfaces for presenting prescreened in-vivo studies. To the extent consistent, any or all of the aspects, embodiments, and examples detailed herein may be used in conjunction with any or all of the other aspects or embodiments detailed herein. [0009] In accordance with aspects of the present disclosure, a system for presenting prescreened in-vivo studies includes at least one processor and at least one memory storing instructions. The instructions, when executed by the at least one processor, cause the system at least to: access a plurality of prescreened in-vivo studies of at least a portion of gastrointestinal tracts (GIT) of patients, where each of the plurality of prescreened in-vivo studies includes respective in-vivo images; access, for each of the plurality of prescreened in-vivo studies, respective prescreening information generated prior to the respective in-vivo images being read by a healthcare professional, where the respective prescreening information includes information on whether one or more GIT conditions were indicated by image prescreening processing of the respective in-vivo images; and provide a graphical user interface configured to present a listing for each of the plurality of prescreened in-vivo studies, where the graphical user interface is configured to present, in each listing, one or more graphical indications corresponding to whether the one or more GIT conditions were indicat