SPECT imaging has been identified as an effective medical modality for diagnosis,
treatment, evaluation and prevention of a range of serious diseases and medical conditions …

Lesion detection is a critical component of disease diagnosis, but the manual segmentation
of lesions in medical images is time-consuming and experience-demanding. These issues …

Feature matching and finding correspondences between endoscopic images is a key step in
many clinical applications such as patient follow-up and generation of panoramic image …

The current methods of auto-segmenting medical images are limited due to insufficient and
ambiguous pathonmorphological labeling. In clinical practice, rough classification labels …

Purpose Quantitative bone single‐photon emission computed tomography (QBSPECT) has
the potential to provide a better quantitative assessment of bone metastasis than planar …

Magnetic resonance imaging (MRI) is commonly used for brain tumor segmentation, which
is critical for patient evaluation and treatment planning. To reduce the labor and expertise …

Retinal edema area, which can be observed in the non-invasive optical coherence
tomography image, is essential for the diagnosis and treatment of many retinal diseases …

To develop a deep image segmentation model that automatically identifies and delineates
lesions of skeletal metastasis in bone scan images, facilitating clinical diagnosis of lung …

Image segmentation plays crucial role in medical image analysis and forms the basis for
clinical diagnosis and patient's treatment planning. But the large variation in organ shapes …

During the last few years, medical image segmentation using deep learning has become the
most active research area in computer vision. Effectively, researchers become more and …