Towards automatic skin cancer detection by
multispectral imaging
For dermatology start-up View Derma we developed a mole inspection camera (multispectral imaging solution). This camera takes multispectral images of skin lesions (10 different wavelengths) that are then classified as malignant or benign.
To develop this classification algorithm we collaborated with the Eindhoven University of Technology. During an internship project, several neural networks were designed and compared. A skin image dataset with annotations was acquired in a clinical study. The networks were trained with different sets of chromophore maps that were computed from the multispectral image stacks. The details and results of this study can be found in the following whitepaper.
On our stand at the Philips Stadion, we engaged with a new generation of engineers about how autonomous systems can contribute to a more sustainable future. Tim Clephas give a presentation of our work on autonomous tractors.
Bram's enthusiasm and dedication prompted Nobleo to support his graduation project focused on reinforcement learning for mobile robot navigation, which later evolved into a whitepaper co-authored with two other Nobleo colleagues. >>>> READ MORE
On our stand at the Philips Stadion, we engaged with a new generation of engineers about how autonomous systems can contribute to a more sustainable future. Tim Clephas give a presentation of our work on autonomous tractors.
Bram's enthusiasm and dedication prompted Nobleo to support his graduation project focused on reinforcement learning for mobile robot navigation, which later evolved into a whitepaper co-authored with two other Nobleo colleagues. >>>> READ MORE