Breast cancer is the most prevalent cancer that affects women all over the world. Early
detection and treatment of breast cancer could decline the mortality rate. Some issues such …

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 …

Objective Uterine smooth muscle hyperplasia causes a tumor called a uterine fibroid. With
an incidence of up to 30%, it is one of the most prevalent tumors in women and has the third …

One of the most prevalent malignant bone tumors is osteosarcoma. The diagnosis and
treatment cycle are long and the prognosis is poor. It takes a lot of time to manually identify …

Background This study was performed to evaluate the clinical feasibility of a U-net for fully
automatic uterine segmentation on MRI by using images of major uterine disorders. Methods …

Abstract Background and Objectives: Image segmentation represents one of the most
challenging issues in medical image analysis to distinguish among different adjacent tissues …

Rationale: High-intensity focused ultrasound (HIFU) therapy represents a noninvasive
surgical approach to treat uterine fibroids. The operation of HIFU therapy relies on the …

Stereotactic neuro‐radiosurgery is a well‐established therapy for intracranial diseases,
especially brain metastases and highly invasive cancers that are difficult to treat with …

Background and objectives: Nowadays, clinical practice in Gamma Knife treatments is
generally based on MRI anatomical information alone. However, the joint use of MRI and …

Accurate segmentation of uterus, uterine fibroids, and spine from MR images is crucial for
high intensity focused ultrasound (HIFU) therapy but remains still difficult to achieve because …