Publications

@misc{Leh20,

title = {Machine Learning based Image Segmentation with Convolutional Neural Networks},

author = {Lehner, Matthias and Benda, Odo },

editor = {Tomaž Jarm, Samo Mahnič-Kalamiza, Aleksandra Cvetkoska, Damijan Miklavčič},

url = {https://www.embec2020.org/wp-content/uploads/2020/11/EMBEC2020_Book_of_Abstracts.pdf},

isbn = {978-961-243-411-3},

year  = {2020},

date = {2020-11-30},

abstract = {In this work, results are presented for a CNN architecture which was developed specifically to classify different segments in CT images of the nasal cavity and paranasal sinuses automatically and accurately. This approach makes it possible to generate high quality segmentations of the frontal, maxillary, and sphenoid sinuses on both sides of the body, the oral and nasal cavities, bone, tissues, as well as the air outside the head surrounding the patient’s body in order to remove the latter conveniently.},

howpublished = {EMBEC Abstract Book Contribution},

keywords = {3D Model Generation, Convolutional Neural Networks, CT Images, nasal cavity},

pubstate = {published},

tppubtype = {misc}

}