5 citations · 10 across the 4 of their papers we have counts for
4 papers
Comparison of Deep Learning Segmentation and Multigrader-annotated Mandibular Canals of Multicenter CBCT scans
Jorma Järnstedt, Jaakko Sahlsten, Joel Jaskari +9
Deep learning approach has been demonstrated to automatically segment the bilateral mandibular canals from CBCT scans, yet systematic studies of its clinical and technical validati…
Uncertainty-aware deep learning methods for robust diabetic retinopathy classification
Joel Jaskari, Jaakko Sahlsten, Theodoros Damoulas +5
Automatic classification of diabetic retinopathy from retinal images has been widely studied using deep neural networks with impressive results. However, there is a clinical need f…
Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading
Jaakko Sahlsten, Joel Jaskari, Jyri Kivinen +4
Diabetes is a globally prevalent disease that can cause visible microvascular complications such as diabetic retinopathy and macular edema in the human eye retina, the images of wh…
A Novel Variational Autoencoder with Applications to Generative Modelling, Classification, and Ordinal Regression
Joel Jaskari, Jyri J. Kivinen
We develop a novel probabilistic generative model based on the variational autoencoder approach. Notable aspects of our architecture are: a novel way of specifying the latent varia…