Detecting skin cancer even before it becomes visible with AI-assisted image recognition
Until now, diagnosing skin tumors has relied on detecting visible changes to the skin, and Line-Field Confocal Optical Coherence Tomography (LC-OCT) is a well-established method used for diagnosis. Now, researchers at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) led by Dr. Moritz Ronicke from the Department of Dermatology at Uniklinikum Erlangen have developed a new approach.
A groundbreaking technique using AI-assisted image recognition is enabling the detection of skin cancer before any visible changes appear on the skin. Conducted by researchers at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), the study introduces a method that systematically screens the faces of high-risk patients for basal cell carcinoma - the most common type of skin cancer worldwide.
This new approach combines Line-Field Confocal Optical Coherence Tomography (LC-OCT) with artificial intelligence to provide real-time, micrometer-scale 3D imaging and probability maps of potential tumors. By detecting basal cell carcinoma even before visible signs develop, the technique allows for less invasive treatment options, with some cases requiring only a topical cream.
Dr. Moritz Ronicke, the lead researcher, emphasizes that early detection enables early intervention, potentially avoiding the need for surgery in many cases. Currently, routine use of this method is hindered by a lack of data on its sensitivity and its time-consuming nature. However, if implemented routinely, this AI-assisted LC-OCT could significantly improve early detection rates and treatment outcomes for skin cancer.
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