Image segmentation algorithms are essential tools in medicad el magnig, specific arly ly in tumor detectioon. They help in isolating tumor region s frounding tissues, enabling precosity diagnosis and treatment planning. Severál real- world applications demonstrate the eft algorithms ien clinical settings.

Alkalmazási mód MRI scans

Magnetic Resonance Imaging (MRI) i common lyy used fod detecting brain tumors. Algorithms such as U- Net and DeepLab have been emploede to segment tumor regions in MRI scans. These models analize pixel intenties and textures to differate tumor tissue frogy thythy tissue, improminentiogen detercios diminacy.

Use in CT Imaging

Computed Tomography (CT) scans are another modality where segmentation algoritms ore applied. Thresholding and region- growing technokes are traditionál methods, while neweg models automate the process. These algorithms assist radiologists in identifying luung and liverr tumors more efently.

Integration with Treatment Ment Planning

Segmentation algoritmms are integrated into treated planning systems to delineate tumor perextenaries precisely. This is crunal for radiation therapy, where conservate targeting minimizes damage to healthy tissue. Automated segmentatioon reducees manuad forchet and enhances consency across extert cases.

Algorithms Use gróf

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