OBJECTIVE: This study aimed to develop an automated method for segmenting spleen computed tomography (CT) images using a deep learning model to address the limitations of manual segmentation, which is known to be susceptible to inter-observer variabi...
BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, posing a significant challenge for individuals and society. Early detection and treatment are essential for effective disease managem...
BACKGROUND: Three-dimensional (3D) whole-heart magnetic resonance imaging (MRI) is an excellent tool to check the heart anatomy of patients with congenital and acquired heart disease. However, most 3D whole-heart MRI acquisitions take a long time to ...
INTRODUCTION: Multimodal medical image fusion techniques play an important role in clinical diagnosis and treatment planning. The process of combining multimodal images involves several challenges depending on the type of modality, transformation tec...
BACKGROUND: Immune checkpoint inhibitor-related pneumonitis (ICI-P) is a fatal adverse event of immunotherapy. However, there is a lack of methods to identify patients who have a high risk of developing ICI-P in immunotherapy.
INTRODUCTION: This paper presents a multichannel deep-learning method for detecting lung diseases using chest X-ray images. Using EfficientNetB0 through EfficientNetB7 pretrained models, the methodology offers improved performance in classifying COVI...
BACKGROUND: Applications of artificial intelligence (AI) in medical ultrasound have rapidly grown in recent years. Therefore, it is necessary to identify and visualize global research trends and hotspots of AI in medical ultrasound to provide guidanc...
BACKGROUND: Patients with malignant tumors often develop bone metastases. SPECT bone scintigraphy is an effective tool for surveying bone metastases due to its high sensitivity, low-cost equipment, and radiopharmaceutical. However, the low spatial re...
BACKGROUND: Brain tumours represent a diagnostic challenge, especially in the imaging area, where the differentiation of normal and pathologic tissues should be precise. The use of up-to-date machine learning techniques would be of great help in term...
OBJECTIVE: This study aimed to establish a multimodal deep-learning network model to enhance the diagnosis of benign and malignant pulmonary ground glass nodules (GGNs).