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The First International Workshop on Multimedia Computing for Health and Medicine is part of the ACM International Conference on Multimedia 2024 (ACM Multimedia 2024). In health and medicine, an immense amount of data is being generated by distributed ...

Many challenges exist in health monitoring and management, such as continuous, accurate, and comfortable monitoring of multi-parameters, early detection and warning of diseases, as well as the interaction with environments. The challenges in healthcare ...

The rapid growth of medical imaging data has far outpaced the availability of trained radiologists, significantly increasing their workload. To alleviate this burden, reduce diagnostic errors, and streamline clinical workflows, the need for automated ...

The need for 3D and 4D (i.e., 3D + time) shape analysis arises in many branches of science ranging from anatomy, bioinformatics, medicine, and biology to computer graphics, multimedia, and virtual and augmented reality. In fact, shape is an essential ...

Fundus imaging is a pivotal tool in ophthalmology, and different imaging modalities are characterized by their specific advantages. For example, Fundus Fluorescein Angiography (FFA) uniquely provides detailed insights into retinal vascular dynamics and ...

Surgical instrument segmentation (SIS) on endoscopic images stands as a long-standing and essential task in the context of computer-assisted interventions for boosting minimally invasive surgery. Given the recent surge of deep learning methodologies and ...

Breast cancer is a complex and often fatal malignancy in women worldwide, requiring thorough medical examinations. Accurately detecting breast cancer is challenging due to its diverse forms, stages, symptoms, and diagnostic techniques. With advancements ...

Most ultrasound image segmentation methods employ a joint training strategy, where the model learns the edge and core regions indiscriminately and uniformly. However, they often overlook the distinct shapes of the edges and the sizes of the core regions. ...

Medical point clouds have rich 3D geometric information for intelligent disease detection. However, it is usually time-consuming and costly to annotate such medical data. In this paper, we propose a novel self-supervised method for intracranial aneurysm ...

Breast ultrasound plays a pivotal role in detecting and diagnosing breast abnormalities. Radiology reports summarize key findings from these examinations, highlighting lesion characteristics and malignancy assessments. However, extracting this critical ...

Deep Neural Networks (DNNs) have successfully uncovered hierarchical functional connectivity networks (FCNs) in the human brain. In particular, the FCNs identified in the deep layers of DNNs usually represent the combinations of traditional FCNs, which ...

Computer-aided cancer survival risk prediction plays an important role in the timely treatment of patients. This is a challenging weakly supervised ordinal regression task associated with multiple clinical factors involved such as pathological images, ...

The significant growth in deepfake technology has triggered concerns over its potential for misuse and ethical consequences. While current literature primarily highlights these risks, this paper offers a unique perspective by exploring the beneficial ...

This research focuses on developing a real-time posture monitoring and risk assessment system for manual lifting tasks using advanced AI and computer vision technologies. Musculoskeletal disorders (MSDs) are a significant concern for workers involved in ...