Gliomas are the most common primary brain malignancies, with different degrees of
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie, …

International challenges have become the de facto standard for comparative assessment of
image analysis algorithms. Although segmentation is the most widely investigated medical …

Performance of models highly depend not only on the used algorithm but also the data set it
was applied to. This makes the comparison of newly developed tools to previously …

Deep learning (DL) models have provided state-of-the-art performance in various medical
imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) …

We present a new experimental framework for the task of Bone Age Assessment (BAA) based
on a local analysis of anatomical Regions Of Interest (ROIs) of hand radiographs. For this …

The reliability of Deep Learning systems depends on their accuracy but also on their robustness
against adversarial perturbations to the input data. Several attacks and defenses have …

Purpose To identify the factors predicting the visual and anatomical outcomes in eyes with
central serous chorioretinopathy (CSCR) through 12 months. Methods Patients with diagnosis …

Lung cancer is by far the leading cause of cancer death in the US. Recent studies have
demonstrated the effectiveness of screening using low dose CT (LDCT) in reducing lung cancer …

Brain lesion segmentation is one of the hardest tasks to be solved in computer vision with an
emphasis on the medical field. We present a convolutional neural network that produces a …

Bone Age Assessment (BAA) is a task performed by radiologists to diagnose abnormal growth
in a child. In manual approaches, radiologists take into account different identity markers …