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 …

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 …

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 …

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 …

In radiotherapy for cancer patients, an indispensable process is to delineate organs-at-risk
(OARs) and tumors. However, it is the most time-consuming step as manual delineation is …

The loss function, also known as cost function, is used for training a neural network or other
machine learning models. Over the past decade, researchers have designed many loss …

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

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