We present a novel method for the joint segmentation of anatomical and functional images.
Our proposed methodology unifies the domains of anatomical and functional images, …

Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19
associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of …

Convolutional neural networks (CNNs) have shown remarkable results over the last several
years for a wide range of computer vision tasks. A new architecture recently introduced by …

Respiratory tract infections are a leading cause of death and disability worldwide. Although
radiology serves as a primary diagnostic method for assessing respiratory tract infections, …

Positron Emission Tomography (PET), a non-invasive functional imaging method at the
molecular level, images the distribution of biologically targeted radiotracers with high sensitivity. …

The emergence of Middle East respiratory syndrome coronavirus (MERS-CoV) as a cause
of severe respiratory disease highlights the need for effective approaches to CoV vaccine …

Routine visual inspection is essential to maintain adequate safety and serviceability of civil
infrastructures. Computer vision and machine learning based software techniques are …

Purpose To organize a multi-institute knee MRI segmentation challenge for characterizing
the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring …

Traffic safety is a major global concern. Helmet usage is a key factor in preventing head
injuries and fatalities caused by motorcycle accidents. However, helmet usage violations …

The computer-based process of identifying the boundaries of lung from surrounding thoracic
tissue on computed tomographic (CT) images, which is called segmentation, is a vital first …