Research output per year
Research output per year
Project Details
Description
Breast cancer is the most common cancer type globally. The survival in low- and middle income countries is poor. An important contributing factor is limited access to breast imaging for a timely diagnosis. In this project, the aim is to develop AI-based decision support for point-of-care-ultrasound that could provide cost effective and accessible breast diagnostics in low-resource settings.
| Status | Finished |
|---|---|
| Effective start/end date | 2022/01/01 → 2024/12/31 |
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
Research output
- 1 Paper in conference proceeding
-
Machine learning algorithm for classification of breast ultrasound images
Karlsson, J., Ramkull, J., Arvidsson, I., Heyden, A., Åström, K., Overgaard, N. C. & Lång, K., 2022 Apr 4, Medical Imaging 2022: Computer-Aided Diagnosis. SPIE, Vol. 12033. 11 p.Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review
Projects
- 1 Finished
-
Breast Cancer Diagnostics in Low Resource Settings Using Point of Care Ultrasound and Deep Learning
Arvidsson, I. (PI), Lång, K. (CoPI), Karlsson, J. (Researcher), Heyden, A. (Researcher), Overgaard, N. C. (Researcher) & Sahlin, F. (Researcher)
Analytic Imaging Diagnostics Arena, AIDA
2024/01/01 → 2024/12/31
Project: Research