image in medicine

INTRODUCTION: Dual phase technetium-99mTc-methoxy isobutyl isonitrile (MIBI) single-photon emission computed tomography with computed tomography (SPECT/CT) may be the most accurate conventional imaging approach for localization of enlarged parathyroid gland (EPG). The imaging is based on the radiopharmaceutical (RP) retention in EPG compared to washout from normal thyroid and normal parathyroid glands. This study aimed to estimate and optimize the contribution of computed tomography (CT) scan and scan range to effective dose (ED) in dual-phase MIBI SPECT/CT parathyroid scintigraphy...

The latest developments in deep learning have demonstrated the importance of CT medical imaging for the classification of pulmonary nodules. However, challenges remain in fully leveraging the relevant medical annotations of pulmonary nodules and distinguishing between the benign and malignant labels of adjacent nodules. Therefore, this paper proposes the Nodule-CLIP model, which deeply mines the potential relationship between CT images, complex attributes of lung nodules, and benign and malignant attributes of lung nodules through a comparative learning method, and optimizes the model in the image feature extraction network by using its similarities and differences to improve its ability to distinguish similar lung nodules...

Lung cancer has seriously threatened human health due to its high lethality and morbidity. Lung adenocarcinoma, in particular, is one of the most common subtypes of lung cancer. Pathological diagnosis is regarded as the gold standard for cancer diagnosis. However, the traditional manual screening of lung cancer pathology images is time consuming and error prone. Computer-aided diagnostic systems have emerged to solve this problem. Current research methods are unable to fully exploit the beneficial features inherent within patches, and they are characterized by high model complexity and significant computational effort...

Semi-supervised deep learning algorithm is an effective means of medical image segmentation. Among these methods, multi-task learning with consistency regularization has achieved outstanding results. However, most of the existing methods usually simply embed the Signed Distance Map (SDM) task into the network, which underestimates the potential ability of SDM in edge awareness and leads to excessive dependence between tasks. In this work, we propose a novel triple-task mutual consistency (TTMC) framework to enhance shape and edge awareness capabilities, and overcome the task dependence problem underestimated in previous work...

Before the Stereotactic Radiosurgery (SRS) treatment, it is of great clinical significance to avoid secondary genetic damage and guide the personalized treatment plans for patients with brain metastases (BM) by predicting the response to SRS treatment of brain metastatic lesions. Thus, we developed a multi-task learning model termed SRTRP-Net to provide prior knowledge of BM ROI and predict the SRS treatment response of the lesion. In dual-encoder tumor segmentation Network (DTS-Net), two parallel encoders encode the original and mirrored multi-modal MRI images...

BACKGROUND & OBJECTIVE: Aortic dissection (AD) is a serious condition requiring rapid and accurate diagnosis. In this study, we aimed to improve the diagnostic accuracy of AD by presenting a novel method for aortic segmentation in computed tomography images that uses a combination of a transformer and a UNet cascade network with a Zoom-Out and Zoom-In scheme (ZOZI-seg). METHODS: The proposed method segments each compartment of the aorta, comprising the true lumen (TL), false lumen (FL), and thrombosis (TH) using a cascade strategy that captures both the global context (anatomical structure) and the local detail texture based on the dynamic patch size with ZOZI schemes...

OBJECTIVES: Essential hypertension is a common chronic condition that can exacerbate or complicate various neurological diseases that may necessitate neuroimaging. Given growing medical imaging costs and the need to understand relationships between population blood pressure control and neuroimaging utilization, we seek to quantify the relationship between maximum blood pressure recorded in a given year and same-year utilization of neuroimaging CT or MR in a large healthcare population...

OBJECTIVES: Computed tomography (CT) and cone beam computed tomography (CBCT) represent the main imaging modalities used in rhinosinusitis patients and are also important in odontogenic sinusitis (OS) diagnostics. Reports, however, often lack information on dentition. Here, we aimed to determine how maxillary dentition is initially interpreted in rhinosinusitis patients' CT/CBCT reports and which dental findings in particular are potentially missed, thus needing more attention. STUDY DESIGN: CT/CBCT scans and radiological reports from 300 rhinosinusitis patients were analysed focusing specifically on dental findings...

The automation of pollen identification has seen vast improvements in the past years, with Convolutional Neural Networks coming out as the preferred tool to train models. Still, only a small portion of works published on the matter address the identification of fossil pollen. Fossil pollen is commonly extracted from organic sediment cores and are used by paleoecologists to reconstruct past environments, flora, vegetation, and their evolution through time. The automation of fossil pollen identification would allow paleoecologists to save both time and money while reducing bias and uncertainty...

INTRODUCTION: This research evaluates the budget impact of treating acute ischaemic stroke (AIS) using a combination of mechanical thrombectomy (MT) with stent retrievers (SR) and intravenous tissue-plasminogen activator (IV-tPA) in Australia. METHODS: This study examined the economic impact over five years for a patient cohort based on the number of patients treated with MT+ IV-tPA in Australia 2021, versus treatment with IV-tPA alone. A budget impact (BI) model was developed to project direct medical costs (economic impact) of IV-tPA+ MT with SR vs...

Workpiece surface defect detection is an indispensable part of intelligent production. The surface information obtained by traditional 2D image detection has some limitations due to the influence of environmental light factors and part complexity. However, the digital twin model has the characteristics of high fidelity and scalability, and the digital twin surface can be obtained by a device with a scanning accuracy of 0.02mm to achieve the representation of the real surface of the workpiece. The surface defect detection system for digital twin models is proposed based on the improved YOLOv5 model in this paper...

The current medical standard for setting an oral cancer (OC) diagnosis is histological examination of a tissue sample taken from the oral cavity. This process is time-consuming and more invasive than an alternative approach of acquiring a brush sample followed by cytological analysis. Using a microscope, skilled cytotechnologists are able to detect changes due to malignancy; however, introducing this approach into clinical routine is associated with challenges such as a lack of resources and experts. To design a trustworthy OC detection system that can assist cytotechnologists, we are interested in deep learning based methods that can reliably detect cancer, given only per-patient labels (thereby minimizing annotation bias), and also provide information regarding which cells are most relevant for the diagnosis (thereby enabling supervision and understanding)...

INTRODUCTION: While there are many papers on maternal and foetal radiation doses from computed tomography pulmonary angiography (CTPA) and ventilation/perfusion (V/Q) lung scanning examinations for diagnosing pulmonary embolism in pregnant patients, few have used clinical data to examine the patient lifetime attributable risk (LAR) of different cancer types. This paper aims to estimate the cancer risk from maternal radiation doses from CTPA and V/Q examinations and associated foetal doses...

Neuroendocrine tumors (NET) are rare malignancies that contain neural and endocrine cells with a median age of diagnosis of 63 years. NETs are typically located in the gastrointestinal (GI) tract, the pancreas, or the lungs. Within the GI tract, the most common locations for NETs are the small bowel, appendix, or rectum. They are often asymptomatic and found incidentally on imaging or during procedures. NETs arising from the left side of the colon are very uncommon. While most NETs are well-differentiated by histology and are slow growing, 7% are poorly differentiated and usually progress rapidly...

Hydrothermally prepared copper-doped carbon dots (Cu-CDs) were modified with Ca2+ , which serve as an excellent platform for the recognition of glycine. The feeble emission of Ca@Cu-CD increases substantially in the presence of glycine due to aggregation-induced emission. At the same time, there was a 5-fold increase in the current response of the Ca@Cu-CD modified electrode as compared to the control. The exceptional combination of fluorescence and conducting properties, along with Ca-glycine interaction, establishes our probe as a dual sensor for the detection of glycine in real serum samples...

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No abstract text is available yet for this article.

IMPORTANCE: Among all US women, breast cancer is the second most common cancer and the second most common cause of cancer death. In 2023, an estimated 43 170 women died of breast cancer. Non-Hispanic White women have the highest incidence of breast cancer and non-Hispanic Black women have the highest mortality rate. OBJECTIVE: The USPSTF commissioned a systematic review to evaluate the comparative effectiveness of different mammography-based breast cancer screening strategies by age to start and stop screening, screening interval, modality, use of supplemental imaging, or personalization of screening for breast cancer on the incidence of and progression to advanced breast cancer, breast cancer morbidity, and breast cancer-specific or all-cause mortality, and collaborative modeling studies to complement the evidence from the review...

IMPORTANCE: Breast cancer is a leading cause of cancer mortality for US women. Trials have established that screening mammography can reduce mortality risk, but optimal screening ages, intervals, and modalities for population screening guidelines remain unclear. OBJECTIVE: To review studies comparing different breast cancer screening strategies for the US Preventive Services Task Force. DATA SOURCES: MEDLINE, Cochrane Library through August 22, 2022; literature surveillance through March 2024...

PURPOSE: To investigate the [68 Ga]DOTATOC PET radiomic profile of head and neck paragangliomas (HNPGLs) and identify radiomic characteristics useful as predictors of succinate dehydrogenase genes (SDHx) pathogenic variants. METHODS: Sporadic and SDHx HNPGL patients, who underwent [68 Ga]DOTATOC PET/CT, were retrospectively included. HNPGLs were analyzed using LIFEx software, and extracted features were harmonized to correct for batch effects and confronted testing for multiple comparison...