Medical image synthesis represents a critical area of research in clinical decision-making,
aiming to overcome the challenges associated with acquiring multiple image modalities for …

Despite advances in data augmentation and transfer learning, convolutional neural
networks (CNNs) difficultly generalise to unseen domains. When segmenting brain scans …

Digital pathology technologies, including whole slide imaging (WSI), have significantly
improved modern clinical practices by facilitating storing, viewing, processing, and sharing …

Cross-modality medical image synthesis is a critical topic and has the potential to facilitate
numerous applications in the medical imaging field. Despite recent successes in deep …

Multimodal medical image registration involves multiple pieces of medical equipment
collecting complementary information on the same content, resulting in information fusion …

Purpose Despite the significant physical differences between magnetic resonance imaging
(MRI) and computed tomography (CT), the high entropy of MRI data indicates the existence …

Multi-modality imaging improves disease diagnosis and reveals distinct deviations in tissues
with anatomical properties. The existence of completely aligned and paired multi-modality …

This chapter gives an overview of the current status of the science of 3D imaging. Loosely,
3D imaging refers to all processing operations that are applied to acquired multidimensional …

Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) are highly distorted by
magnetic field inhomogeneities. Distortion and differences in image contrast between EPI …

The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal
Processing Society (SPS) promotes activities within the broad technical field of biomedical …