The loss function is an important component in deep learning-based segmentation methods.
Over the past five years, many loss functions have been proposed for various segmentation …

Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence
of disruptive technical advances and impressive experimental results, notably in the field of …

The real-time reverse transcription-polymerase chain reaction (RT-PCR) detection of viral
RNA from sputum or nasopharyngeal swab had a relatively low positive rate in the early …

Automatic segmentation methods are an important advancement in medical image analysis.
Machine learning techniques, and deep neural networks in particular, are the state-of-the-art …

We propose a generalized focal loss function based on the Tversky index to address the
issue of data imbalance in medical image segmentation. Compared to the commonly used …

COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing
life around the world to a frightening halt and claiming thousands of lives. Due to COVID …

Accurate and automatic segmentation of medical images is a crucial step for clinical
diagnosis and analysis. The convolutional neural network (CNN) approaches based on the …

Widely used loss functions for convolutional neural network (CNN) segmentation, eg, Dice
or cross-entropy, are based on integrals (summations) over the segmentation regions …

Background: Over half a million individuals are diagnosed with head and neck cancer each
year globally. Radiotherapy is an important curative treatment for this disease, but it requires …

Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …