Glioblastoma (GBM) is a highly invasive brain tumor, whose cells infiltrate surrounding
normal brain tissue beyond the lesion outlines visible in the current medical scans. These …

Cancer of unknown primary (CUP) origin is an enigmatic group of diagnoses in which the
primary anatomical site of tumour origin cannot be determined 1 , 2 . This poses a …

Automatic segmentation of the liver and hepatic lesions is an important step towards
deriving quantitative biomarkers for accurate clinical diagnosis and computer-aided decision …

Gliomas are the most common primary brain malignancies, with different degrees of
aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, ie, …

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS),
which was organized in conjunction with the IEEE International Symposium on …

In oncology, the patient state is characterized by a whole spectrum of modalities, ranging
from radiology, histology, and genomics to electronic health records. Current artificial …

In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models stratified …

The rapidly emerging field of computational pathology has demonstrated promise in developing
objective prognostic models from histology images. However, most prognostic models …

Endomyocardial biopsy (EMB) screening represents the standard of care for detecting allograft
rejections after heart transplant. Manual interpretation of EMBs is affected by substantial …

Deep Learning-based computational pathology algorithms have demonstrated profound
ability to excel in a wide array of tasks that range from characterization of well known …