Deep learning has been extensively applied to segmentation in medical imaging. U‐Net
proposed in 2015 shows the advantages of accurate segmentation of small targets and its …

Deep learning (DL) is a branch of machine learning and artificial intelligence that has been
applied to many areas in different domains such as health care and drug design. Cancer …

Discrimination of ovarian tumors is necessary for proper treatment. In this study, we
developed a convolutional neural network model with a convolutional autoencoder (CNN …

In the recent era, Image processing has been one of the most commonly used domain in the
field of medical science that includes different kinds of procedures namely extraction, image …

Lung nodules are abnormal growths and lesions may exist. Both lungs may have nodules.
Most lung nodules are harmless (not cancerous/malignant). Pulmonary nodules are rare in …

Purpose The current study aimed to evaluate the association of endorectal ultrasound (EUS)
radiomics features at different denoising filters based on machine learning algorithms and to …

Purpose The study aimed to develop the open-source body and organ analysis (BOA), a
comprehensive computed tomography (CT) image segmentation algorithm with a focus on …

Ovarian cancer is the gynecological malignant tumor with low early diagnosis rate and high
mortality. Automated and reliable segmentation of ovarian tumor plays an essential role in …

Simple Summary Non-invasive imaging modalities are commonly used in clinical practice.
Recently, the application of machine learning (ML) techniques has provided a new scope for …

Difficulty in detecting tumours in early stages is the major cause of mortalities in patients,
despite the advancements in treatment and research regarding ovarian cancer. Deep …