Deep Learning on Ultrasound Images Visualizes the Femoral Nerve with Good Precision

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Berggreen, JohanLund University,Lunds universitet,Medicinsk teknik, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,LTH profilområde: Teknik för hälsa,LTH profilområden,Lunds Tekniska Högskola,Biomedical Engineering, Lund,Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,LTH Profile Area: Engineering Health,LTH Profile areas,Faculty of Engineering, LTH,Skåne University Hospital (author)

Deep Learning on Ultrasound Images Visualizes the Femoral Nerve with Good Precision

Article/chapterEnglish2023

Publisher, publication year, extent ...

2023-01-07
MDPI AG,2023

Numbers

LIBRIS-ID:oai:lup.lub.lu.se:182e3260-0e78-442d-b4cf-391332ec4163
https://lup.lub.lu.se/record/182e3260-0e78-442d-b4cf-391332ec4163URI
https://doi.org/10.3390/healthcare11020184DOI

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Language:English
Summary in:English

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SwePubSwePub

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Subject category:art swepub-publicationtype
Subject category:ref swepub-contenttype

Notes

The number of hip fractures per year worldwide is estimated to reach 6 million by the year 2050. Despite the many advantages of regional blockades when managing pain from such a fracture, these are used to a lesser extent than general analgesia. One reason is that the opportunities for training and obtaining clinical experience in applying nerve blocks can be a challenge in many clinical settings. Ultrasound image guidance based on artificial intelligence may be one way to increase nerve block success rate. We propose an approach using a deep learning semantic segmentation model with U-net architecture to identify the femoral nerve in ultrasound images. The dataset consisted of 1410 ultrasound images that were collected from 48 patients. The images were manually annotated by a clinical professional and a segmentation model was trained. After training the model for 350 epochs, the results were validated with a 10-fold cross-validation. This showed a mean Intersection over Union of 74%, with an interquartile range of 0.66–0.81.

Subject headings and genre

MEDICIN OCH HÄLSOVETENSKAP Klinisk medicin Radiologi och bildbehandling hsv//swe
MEDICAL AND HEALTH SCIENCES Clinical Medicine Radiology, Nuclear Medicine and Medical Imaging hsv//eng
artificial intelligence
deep learning
hip fracture
nerve blocks
ultrasound

Added entries (persons, corporate bodies, meetings, titles ...)

Johansson, AndersLund University,Lunds universitet,Medicinsk teknik, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,LTH profilområde: Teknik för hälsa,LTH profilområden,Lunds Tekniska Högskola,Biomedical Engineering, Lund,Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,LTH Profile Area: Engineering Health,LTH Profile areas,Faculty of Engineering, LTH(Swepub:lu)anes-ajo (author)
Jahr, JohnLund University,Lunds universitet,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Department of Clinical Sciences, Lund,Faculty of Medicine(Swepub:lu)anes-jja (author)
Möller, SebastianLund University,Lunds universitet,Medicinsk teknik, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,LTH profilområde: Teknik för hälsa,LTH profilområden,Lunds Tekniska Högskola,LU profilområde: Ljus och material,Lunds universitets profilområden,Biomedical Engineering, Lund,Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,LTH Profile Area: Engineering Health,LTH Profile areas,Faculty of Engineering, LTH,LU Profile Area: Light and Materials,Lund University Profile areas,Region Skåne(Swepub:lu)se6152st (author)
Jansson, TomasLund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Medicinsk teknik, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,LTH profilområde: Teknik för hälsa,LTH profilområden,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH,Biomedical Engineering, Lund,Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,LTH Profile Area: Engineering Health,LTH Profile areas,Faculty of Engineering, LTH,Region Skåne(Swepub:lu)elma-tja (author)
Medicinsk teknik, LundSektion V (creator_code:org_t)

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In:Healthcare (Switzerland): MDPI AG11:22227-9032

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