Metal Artifact Reduction In Cone-Beam Extremity Images Using Gated Convolutions. - Harshit Agrawal; Ari Hietanen; Simo Särkkä (ISBI, 2021)

Comparison of Deep Learning Segmentation and Multigrader-annotated Mandibular Canals of Multicenter CBCT scans. - Jorma Järnstedt; Jaakko Sahlsten; Joel Jaskari; Kimmo Kaski; Helena Mehtonen; Ziyuan Lin; Ari Hietanen; Osku Sundqvist; Vesa Varjonen; Vesa Mattila; Sangsom Prapayasotok; Sakarat Nalampang (CoRR, 2022)

Metal artifact correction in cone beam computed tomography using synthetic X-ray data. - Harshit Agrawal; Ari Hietanen; Simo Särkkä (CoRR, 2022)

Deep Learning Based Projection Domain Metal Segmentation for Metal Artifact Reduction in Cone Beam Computed Tomography. - Harshit Agrawal; Ari Hietanen; Simo Särkkä (IEEE Access, 2023)

Reproducibility analysis of automated deep learning based localisation of mandibular canals on a temporal CBCT dataset. - Jorma Järnstedt; Jaakko Sahlsten; Joel Jaskari; Kimmo Kaski; Helena Mehtonen; Ari Hietanen; Osku Sundqvist; Vesa Varjonen; Vesa Mattila; Sangsom Prapayasotok; Sakarat Nalampang (CoRR, 2023)

The Optimization of the Light-Source Spectrum Utilizing Neural Networks for Detecting Oral Lesions. - Kenichi Ito; Hiroshi Higashi; Ari Hietanen; Pauli Fält; Kyoko Hine; Markku Hauta-Kasari; Shigeki Nakauchi (J. Imaging, 2023)