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Indocyanine green dyed gauze-guided minimum invasive surgery for anatomical landmarks and preventing gauze remnants: a pilot study.
Langenbecks Arch Surg
January 2025
Department of Chemical Science & Engineering, School of Materials and Chemical Technology, Institute of Science Tokyo, 2-12-1 Ookayama, Meguro-ku, Tokyo, 152-8552, Japan.
Purpose: We aimed to develop a novel fluorescent surgical gauze dyed with indocyanine green (ICG) to guide surgeons to the target anatomical destination during surgery for real-time navigation and to prevent gauze remnants after surgery.
Methods: Surgical gauze was dyed with an aqueous solution of ICG (5.0 × 10 mol L for Steraze, 1.
Patch-Wise Deep Learning Method for Intracranial Stenosis and Aneurysm Detection-the Tromsø Study.
Neuroinformatics
January 2025
Department of Clinical Medicine, UiT the Arctic University of Norway, Tromsø, Norway.
Intracranial atherosclerotic stenosis (ICAS) and intracranial aneurysms are prevalent conditions in the cerebrovascular system. ICAS causes a narrowing of the arterial lumen, thereby restricting blood flow, while aneurysms involve the ballooning of blood vessels. Both conditions can lead to severe outcomes, such as stroke or vessel rupture, which can be fatal.
View Article and Find Full Text PDFCXR-LLaVA: a multimodal large language model for interpreting chest X-ray images.
Eur Radiol
January 2025
Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Objective: This study aimed to develop an open-source multimodal large language model (CXR-LLaVA) for interpreting chest X-ray images (CXRs), leveraging recent advances in large language models (LLMs) to potentially replicate the image interpretation skills of human radiologists.
Materials And Methods: For training, we collected 592,580 publicly available CXRs, of which 374,881 had labels for certain radiographic abnormalities (Dataset 1) and 217,699 provided free-text radiology reports (Dataset 2). After pre-training a vision transformer with Dataset 1, we integrated it with an LLM influenced by the LLaVA network.
White Matter Tract Crossing and Bottleneck Regions in the Fetal Brain.
Hum Brain Mapp
January 2025
Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, Massachusetts, USA.
There is a growing interest in using diffusion MRI to study the white matter tracts and structural connectivity of the fetal brain. Recent progress in data acquisition and processing suggests that this imaging modality has a unique role in elucidating the normal and abnormal patterns of neurodevelopment in utero. However, there have been no efforts to quantify the prevalence of crossing tracts and bottleneck regions, important issues that have been investigated for adult brains.
View Article and Find Full Text PDFDeep Learning and Multidisciplinary Imaging in Pediatric Surgical Oncology: A Scoping Review.
Cancer Med
January 2025
Department of Pediatric Surgery, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Background: Medical images play an important role in diagnosis and treatment of pediatric solid tumors. The field of radiology, pathology, and other image-based diagnostics are getting increasingly important and advanced. This indicates a need for advanced image processing technology such as Deep Learning (DL).
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