Enhancing Diagnostic Precision: Saliency Detection in Medical Imaging for Improved Efficiency
Fuente:
Zenodo
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Recurso digital |
| Sprache: | Englisch |
| Veröffentlicht: |
Zenodo
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866901131578310656 |
|---|---|
| author | IJESAT - International journal of Engineering sciences and Advanced Technology |
| author_facet | IJESAT - International journal of Engineering sciences and Advanced Technology |
| contents | <p><span>Medical professionals are facing challenges in analyzing unclear medical images, which complicates the identification of tissue problems of the patient. Generally, medical professionals analyze large volumes of medical images manually. It causes a lot of time which delays in diagnosis. Small or irregular abnormalities are difficult to detect manually. In this research paper, we are proposing a solution for the above problems by the study of "Saliency Detection." Saliency detection is a technique that helps to show the important parts of the medical images. This gives rapid identification of abnormalities and highlights the critical regions in medical images. This minimizes human errors and increases the effectiveness of patient care. Saliency detection provides clear and focused views of essential image areas and thereby increases the reliability of the diagnosis. Saliency detection can be achieved by using machine learning algorithms like CNN & U-Net. Recent advances ensure more accurate & quicker results.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15179867 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Enhancing Diagnostic Precision: Saliency Detection in Medical Imaging for Improved Efficiency IJESAT - International journal of Engineering sciences and Advanced Technology Saliency detection machine learning abnormalities, healthcare <p><span>Medical professionals are facing challenges in analyzing unclear medical images, which complicates the identification of tissue problems of the patient. Generally, medical professionals analyze large volumes of medical images manually. It causes a lot of time which delays in diagnosis. Small or irregular abnormalities are difficult to detect manually. In this research paper, we are proposing a solution for the above problems by the study of "Saliency Detection." Saliency detection is a technique that helps to show the important parts of the medical images. This gives rapid identification of abnormalities and highlights the critical regions in medical images. This minimizes human errors and increases the effectiveness of patient care. Saliency detection provides clear and focused views of essential image areas and thereby increases the reliability of the diagnosis. Saliency detection can be achieved by using machine learning algorithms like CNN & U-Net. Recent advances ensure more accurate & quicker results.</span></p> |
| title | Enhancing Diagnostic Precision: Saliency Detection in Medical Imaging for Improved Efficiency |
| topic | Saliency detection machine learning abnormalities, healthcare |
| url | https://doi.org/10.5281/zenodo.15179867 |