2 citations · 2 across the 3 of their papers we have counts for
3 papers · 1 filter
cRedAnno+: Annotation Exploitation in Self-Explanatory Lung Nodule Diagnosis
Jiahao Lu, Chong Yin, Kenny Erleben +2
Recently, attempts have been made to reduce annotation requirements in feature-based self-explanatory models for lung nodule diagnosis. As a representative, cRedAnno achieves compe…
Auto-segmentation of Hip Joints using MultiPlanar UNet with Transfer learning
Peidi Xu, Faezeh Moshfeghifar, Torkan Gholamalizadeh +3
Accurate geometry representation is essential in developing finite element models. Although generally good, deep-learning segmentation approaches with only few data have difficulti…
Reducing Annotation Need in Self-Explanatory Models for Lung Nodule Diagnosis
Jiahao Lu, Chong Yin, Oswin Krause +3
Feature-based self-explanatory methods explain their classification in terms of human-understandable features. In the medical imaging community, this semantic matching of clinical…