8 citations · 9 across the 5 of their papers we have counts for
7 papers
Is MC Dropout Bayesian?
Loic Le Folgoc, Vasileios Baltatzis, Sujal Desai +7
MC Dropout is a mainstream "free lunch" method in medical imaging for approximate Bayesian computations (ABC). Its appeal is to solve out-of-the-box the daunting task of ABC and un…
Voxel-level Importance Maps for Interpretable Brain Age Estimation
Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Alexander Hammers +1
Brain aging, and more specifically the difference between the chronological and the biological age of a person, may be a promising biomarker for identifying neurodegenerative disea…
The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification
Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loic Le Folgoc +6
Using publicly available data to determine the performance of methodological contributions is important as it facilitates reproducibility and allows scrutiny of the published resul…
The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data
Vasileios Baltatzis, Loic Le Folgoc, Sam Ellis +6
Convolutional Neural Networks (CNNs) are widely used for image classification in a variety of fields, including medical imaging. While most studies deploy cross-entropy as the loss…
Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data
Loic Le Folgoc, Vasileios Baltatzis, Amir Alansary +8
Datasets are rarely a realistic approximation of the target population. Say, prevalence is misrepresented, image quality is above clinical standards, etc. This mismatch is known as…
Patch-based Brain Age Estimation from MR Images
Kyriaki-Margarita Bintsi, Vasileios Baltatzis, Arinbjörn Kolbeinsson +2
Brain age estimation from Magnetic Resonance Images (MRI) derives the difference between a subject's biological brain age and their chronological age. This is a potential biomarker…