Catarina Olimpio, Ida Paramonov, Leslie Matalonga, Steven Laurie, Katherine Schon, Kiran Polavarapu, Janbernd Kirschner, Ulrike Schara-Schmidt, Hanns Lochmüller, Patrick F Chinnery, Rita Horvath
Increased Diagnostic Yield by Reanalysis of Whole Exome Sequencing Data in Mitochondrial Disease
Journal of neuromuscular diseases
facial acne prevalent dermatological condition regularly observed general population however important detect acne early condition worsen treated purpose deeplearningbased methods proposed automate detection acquiring acne training data easy therefore study proposes novel deep learning model facial acne segmentation utilizing semisupervised learning method known bidirectional copypaste synthesizes images interchanging foreground background parts labeled unlabeled images training phase overcome lower performance observed labeled image training part compared previous methods new framework devised directly compute training loss based labeled images effectiveness proposed method evaluated previous semisupervised learning methods using images cropped facial images acne sites proposed method achieved dice score 05205 experiments utilizing 3 labels marking improvement 00151 00473 dice score previous methods proposed semisupervised learning approach facial acne segmentation demonstrated improvement performance offering novel direction future acne analysis