Peng Liu, Svea Steuer, Jonas Golde, Joseph Morgenstern, Yujia Hu, Catherina Schieffer, Steffen Ossmann, Lars Kirsten, Sebastian Bodenstedt, Micha Pfeiffer, Stefanie Speidel, Edmund Koch, Marcus Neudert
Endoscopic optical coherence tomography (OCT) offers a non-invasive approach to perform the morphological and functional assessment of the middle ear in vivo. However, interpreting such OCT images is challenging and time-consuming due to the shadowing of preceding structures. Deep neural networks have emerged as a promising tool to enhance this process in multiple aspects, including segmentation, classification, and registration. Nevertheless, the scarcity of annotated datasets of OCT middle ear images poses a significant hurdle to the performance of neural networks...
February 26, 2024: Scientific Data