Artificial Intelligence Applications

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Advanced Artificial Intelligence Applications in Radiology

The advanced artificial intelligence applications used at our center are software solutions developed to support the radiologist’s evaluation process. These systems assist with quantitative measurements of images, comparisons with previous examinations, and more careful assessment of certain findings that may be difficult to detect with the human eye.

Artificial intelligence applications are supportive tools that provide physicians with additional data during the diagnostic and reporting process. The final evaluation and reporting are always performed by a radiologist. This approach may contribute to more standardized, comparable, and detailed assessments, particularly in conditions requiring follow-up.

Artificial Intelligence Applications in Brain Imaging

  • Automatic measurement and quantitative assessment of brain volume
  • Support in evaluating patterns of volume loss in Alzheimer’s disease and other forms of dementia
  • Analyses that assist in distinguishing changes associated with normal aging from disease-related changes
  • Monitoring lesion burden in patients with multiple sclerosis (MS)
  • Support in detecting newly developed, enlarging, or regressing lesions through comparison with previous examinations

In Brain Tumor Follow-up

  • Measurements that assist in monitoring changes in tumor volume
  • Contributing to a more objective assessment of changes in mass size over time during post-treatment follow-up

In Breast Imaging

  • Applications that assist with artificial intelligence-supported analysis of breast images
  • Support for the reporting process in accordance with the BI-RADS assessment system

In Prostate Imaging

  • Analyses that assist in the evaluation of lesions on prostate MRI examinations
  • Support for the reporting process according to the PI-RADS system

In Lung Imaging

  • Software that assists in the evaluation of pulmonary nodules, masses, and fibrotic changes
  • Support for monitoring changes in size, extent, or appearance through comparative analysis with previous examinations
  • Contributing to a more systematic assessment of findings that may require attention for progression in certain cases

Advanced artificial intelligence applications in radiology are not systems that replace the physician, but rather supportive technologies that enhance the physician’s evaluation. At our center, these technologies are used together with the expertise of our radiologists to contribute to more detailed, comparable, and standardized assessments.

“Artificial intelligence supports the physician; the final decision is made by the physician.”

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F.A.Q

Frequently Asked Questions About Artificial Intelligence Applications

We have compiled the most frequently asked questions about advanced artificial intelligence applications in radiology. Here, you can find answers to a wide range of questions—from AI's role in imaging technologies and its contribution to diagnostic processes to issues regarding safety and areas of application.

Radyolojide yapay zeka, tıbbi görüntülerin analiz edilmesine yardımcı olan gelişmiş yazılımlar ve algoritmaların kullanılmasıdır. Bu sistemler, görüntülerdeki anormallikleri daha hızlı ve doğru şekilde tespit etmeye yardımcı olabilir.

Yapay zeka, röntgen, MR, BT ve diğer görüntüleme yöntemlerinden elde edilen verileri analiz ederek doktorlara destek sağlar. Özellikle erken teşhis, görüntü yorumlama ve raporlama süreçlerinde önemli bir rol oynar.

Yapay zeka, görüntüleri daha hızlı analiz edebilir, küçük veya erken aşamadaki bulguları fark etmeye yardımcı olabilir ve tanı sürecinin daha verimli ilerlemesini sağlayabilir.

Yapay zeka; akciğer hastalıkları, tümörler, kemik kırıkları, damar hastalıkları ve bazı nörolojik durumların görüntüler üzerinden değerlendirilmesinde yardımcı olabilir.

Sağlık alanında kullanılan yapay zeka sistemleri belirli standartlara ve kalite kontrollerine tabidir. Bu sistemler doktorların karar sürecini desteklemek amacıyla güvenli şekilde geliştirilir.

Evet, yapay zeka görüntüleri hızlı şekilde analiz edebildiği için bazı durumlarda raporlama sürecinin daha hızlı ilerlemesine yardımcı olabilir.

Yapay zeka sistemleri geniş veri setleriyle eğitildiği için yüksek doğruluk oranlarına ulaşabilir. Ancak kesin tanı ve yorum her zaman radyoloji uzmanı tarafından yapılır.