Latest AI and machine learning research in pathology for healthcare professionals.
Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic diagnosis of c...
Histopathological whole slide images of haematoxylin and eosin (H&E)-stained biopsies contain valuab...
Bioinspired soft robotic systems that mimic living organisms using engineered muscle tissue and biom...
Breast cancer is the most diagnosed cancer among women around the world. The development of computer...
Tissue diagnostics is the world of pathologists, and it is increasingly becoming digitalised to leve...
Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. While there are a number of ...
The diagnosis of cervical dysplasia, carcinoma in situ and confirmed carcinoma cases is more easily ...
OBJECTIVE: The microscopic review of hematoxylin-eosin-stained images of focal cortical dysplasia ty...
There is a growing need for fast and accurate methods for testing developmental neurotoxicity across...
Recently, the inflammation of the intestinal mucosa has been related to many diseases in humans and ...
PURPOSE: The type of pituitary adenoma (PA) cannot be clearly recognized with preoperative magnetic ...
Optical tissue transparency permits scalable cellular and molecular investigation of complex tissues...
For intravascular OCT (IVOCT) images, we developed an automated atherosclerotic plaque characterizat...
To assist radiologists in breast cancer classification in automated breast ultrasound (ABUS) imaging...
Cell image classification methods are currently being used in numerous applications in cell biology ...
OBJECTIVE: Genetic diagnosis of muscular dystrophies (MDs) has classically been guided by clinical p...
BACKGROUND AND PURPOSE: Multiparametric radiological imaging is vital for detection, characterizatio...
Thyroid cancer is a disease in which the first symptom is a nodule in the thyroid region of the neck...
Acute lymphoblastic leukemia (ALL) is a pervasive pediatric white blood cell cancer across the globe...
Currently methods for predicting absorbed dose after administering a radiopharmaceutical are rather ...
Digital histology images are amenable to the application of convolutional neural networks (CNNs) for...