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Implicit neural representation-based method for metal-induced beam hardening artifact reduction in X-ray CT imaging.
Med Phys
January 2025
National Institute for Mathematical Sciences, Daejeon, Republic of Korea.
Background: In X-ray computed tomography (CT), metal-induced beam hardening artifacts arise from the complex interactions between polychromatic X-ray beams and metallic objects, leading to degraded image quality and impeding accurate diagnosis. A previously proposed metal-induced beam hardening correction (MBHC) method provides a theoretical framework for addressing nonlinear artifacts through mathematical analysis, with its effectiveness demonstrated by numerical simulations and phantom experiments. However, in practical applications, this method relies on precise segmentation of highly attenuating materials and parameter estimations, which limit its ability to fully correct artifacts caused by the intricate interactions between metals and other dense materials, such as bone or teeth.
View Article and Find Full Text PDFMultilevel perception boundary-guided network for breast lesion segmentation in ultrasound images.
Med Phys
January 2025
Engineering Research Center of Text Computing & Cognitive Intelligence, Ministry of Education, Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, China.
Background: Automatic segmentation of breast tumors from the ultrasound images is essential for the subsequent clinical diagnosis and treatment plan. Although the existing deep learning-based methods have achieved considerable progress in automatic segmentation of breast tumors, their performance on tumors with similar intensity to the normal tissues is still not satisfactory, especially for the tumor boundaries.
Purpose: To accurately segment the non-enhanced lesions with more accurate boundaries, a novel multilevel perception boundary-guided network (PBNet) is proposed to segment breast tumors from ultrasound images.
Outcomes of Zero Power Intraocular Lenses: Insights into the Keratometric Index and Axial Length.
J Cataract Refract Surg
January 2025
Aros Private Hospital, Aarhus, Denmark (Olsen).
Purpose: We analyzed intraocular lens (IOL) power calculation in a series of patients with a zero diopter power implant. The idea was to bypass the Estimated Lens Plane (ELP), an important variable in normal IOL calculation.
Setting: Large multi-center group practice.
Impact of introducing transnasal endoscopy on expanding diagnostic endoscopy services.
BMJ Open Qual
January 2025
Department of Gastroenterology, University Hospital Llandough, Llandough, South Glamorgan, UK
Introduction: Demand for endoscopic services is outstripping capacity in the UK. Transnasal endoscopy (TNE) utilises a narrow calibre endoscope to pass through the nasal passages, thereby reducing retching and discomfort. It is better tolerated compared with standard transoral endoscopy (TOE) but is still rarely used as a diagnostic modality.
View Article and Find Full Text PDFDeep Learning-Powered CT-Less Multitracer Organ Segmentation From PET Images: A Solution for Unreliable CT Segmentation in PET/CT Imaging.
Clin Nucl Med
January 2025
From the Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland.
Purpose: The common approach for organ segmentation in hybrid imaging relies on coregistered CT (CTAC) images. This method, however, presents several limitations in real clinical workflows where mismatch between PET and CT images are very common. Moreover, low-dose CTAC images have poor quality, thus challenging the segmentation task.
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