Multi-branch CNN and grouping cascade attention for medical image classification.

Visual Transformers(ViT) have made remarkable achievements in the field of medical image analysis. However, ViT-based methods have poor classification results on some small-scale medical image classification datasets. Meanwhile, many ViT-based models sacrifice computational cost for superior performance, which is a great challenge in practical clinical applications. In this paper, we propose an efficient medical image classification network based on an alternating mixture of CNN and Transformer tandem, which is called Eff-CTNet. Specifically, the existing ViT-based method still mainly relies on multi-head self-attention (MHSA). Among them, the attention maps of MHSA are highly similar, which leads to computational redundancy. Therefore, we propose a group cascade attention (GCA) module to split the feature maps, which are provided to different attention heads to further improves the diversity of attention and reduce the computational cost. In addition, we propose an efficient CNN (EC) module to enhance the ability of the model and extract the local detail information in medical images. Finally, we connect them and design an efficient hybrid medical image classification network, namely Eff-CTNet. Extensive experimental results show that our Eff-CTNet achieves advanced classification performance with less computational cost on three public medical image classification datasets.

[A Survey of the Current Status and the Needs of Medical Imaging Technicians in China]. / ä¸­å›½åŒ»å­¦å½±åƒæŠ€æœ¯ä»Žä¸šäººå‘˜çŽ°çŠ¶å’Œéœ€æ±‚è°ƒæŸ¥ç ”ç©¶.

Objective: To investigate the status quo and the needs of medical imaging technicians (MITs) in the radiology department of secondary and tertiary hospitals in China, so as to provide references and support for the development of the medical imaging technology industry and the relevant policymaking by health administrative departments. Methods: The questionnaire was developed by the Chinese Society of Imaging Technology. The radiology department of each hospital involved in the survey recommended one MIT to fill out the online questionnaire. The contents included: (a) the basic information of the hospital; (b) a general overview of the MITs in the hospital; (c) daily work; (d) career development and promotion; (e) research status and needs, etc. Differences in the number of MIT staff were compared using the Mann-Whitney U test and the chi-square test was used to compare the differences in the selected numbers of MITs in need between regions or between different levels of hospitals. Results: In this investigation, valid questionnaires were finally obtained from a total of 5403 hospitals in 31 provinces in China. The total number of MITs of the hospitals covered in the sample was 67481. The number of MITs in each hospital was 9 (5, 16). The male-to-female ratio was 1.41:1. MITs who were 20 to 40 years old accounted for 78%. The proportions of MITs who had completed doctorate, master's, undergraduate, junior college, and technical secondary school or lower level education were 0.6%, 3.3%, 60.7%, 30.8%, and 4.55%, respectively. The proportions of chief MITs, deputy chief MITs, supervisor MITs, primary MITs, assistant technician and those below were 1.0%, 4.21%, 22.1%, 51.8%, and 20.9%, respectively. The overall professional satisfaction of MITs was good. "Lack of opportunities for learning and communication" was quoted as the main problem MITs encountered in regard to improving their job-related competency. 59.2% of the respondents had not published any academic papers in the past five years, and only 7.0% of the respondents had published in journals included in the Science Citation Index (SCI) in the past five years. Conclusion: MITs in China are on average relatively young and the number of MITs has greatly increased. At this stage, more attention should be given to the cultivation of talents and continuing education of MITs and the construction of the discipline should be further strengthened, so as to provide strong support for the development of the medical imaging technology industry in China.

Comunicação na transferência de cuidados para realização de exames de imagem na ótica da enfermagem / Communication in the transfer of care for imaging exams from a nursing perspective / Comunicación en la transferencia de cuidados para exámenes por imágenes desde la perspectiva de enfermería

Objetivo:analisar a percepção de profissionais de enfermagem sobre a comunicação entre equipes na transferência de cuidados de pacientes para a realização de exames de imagem. Método:pesquisa exploratório-descritiva, qualitativa, realizada com 43 profissionais de enfermagem de um complexo hospitalar de Porto Alegre, entre junho e agosto de 2021. Os dados foram coletados por entrevista semiestruturada e utilizou-se Análise de Conteúdo de Minayo. Resultados:emergiram três temas: como ocorre o processo de comunicação para a transferência do paciente internado ao setor de exames; as potencialidades e fragilidades deste processo e ferramentas para qualificar a comunicação. O enfermeiro atua como articulador da comunicação, que ora ocorre utilizando ferramentase com etapas verbais/telefônicas. O sistema de notas de transferência, a dupla checagem e o readbackpossuem falhas, por não serem oficializados nem específicos. Conclusões:os profissionais consideram a comunicação verbal como a maior fragilidade e sugerem ferramentas formais para torná-la efetiva.

Objective:to analyze the perception of nursing professionals regarding communication between teams in the transfer of patient care for imaging examinations. Method:exploratory-descriptive research, qualitative, conducted with 43 nursing professionals from a hospital complex in Porto Alegre, between June and August 2021. Data were collected through semi-structured interviews and analyzed using Minayo's Content Analysis. Results: three themes emerged: how the communication process occurs for the transfer of the hospitalized patient to the examination department; the strengths and weaknesses of this process; and tools to enhance communication. The nurse acts as a communication facilitator, sometimes using tools and verbal/phone methods. The transfer note system, double-checking, and read-back have flaws because they are not formalized nor specific. Conclusions: professionals consider verbal communication the major weakness and suggest formal tools to make it more effective

Objetivo: analizar la percepción de profesionales de enfermería sobre la comunicación entre equipos al momento de transferir la atención al paciente para la realización de exámenes de imagen.Método: investigación realizada con 43 profesionales de enfermería de un complejo hospitalario de Porto Alegre, entre junio y agosto de 2021. Entrevistas semiestructuradas ocurrieron y se utilizó el análisis de contenido. Resultados: surgieron tres temas: cómo ocurre el proceso de comunicación para la transferencia delpaciente hospitalizado al departamento de exámenes; las potencialidades y debilidades de este proceso y las herramientas para cualificar la comunicación. El enfermero actúa como articulador de la comunicación, que en ocasiones ocurre mediante herramientasy pasos verbales/telefónicos. El sistema de notas de transferencia, la doble verificación y la relectura tienen fallas, pues no son oficiales ni específicos. Conclusiones: los profesionales consideran la comunicación verbal como la mayor debilidad y sugieren herramientas formales para hacerla efectiva.

Optimizing Advanced Imaging of the Pediatric Patient in the Emergency Department: Policy Statement.

Advanced imaging, including ultrasonography, computed tomography, and magnetic resonance imaging (MRI), is an integral component to the evaluation and management of ill and injured children in the emergency department. As with any test or intervention, the benefits and potential impacts on management must be weighed against the risks to ensure that high-value care is being delivered. There are important considerations specific to the pediatric patient related to the ordering and interpretation of advanced imaging. This policy statement provides guidelines for institutions and those who care for children to optimize the use of advanced imaging in the emergency department setting and was coauthored by experts in pediatric and general emergency medicine, pediatric radiology, and pediatric surgery. The intent is to guide decision-making where children may access care.

Optimizing Advanced Imaging of the Pediatric Patient in the Emergency Department: Technical Report.

Advanced diagnostic imaging modalities, including ultrasonography, computed tomography, and magnetic resonance imaging (MRI), are key components in the evaluation and management of pediatric patients presenting to the emergency department. Advances in imaging technology have led to the availability of faster and more accurate tools to improve patient care. Notwithstanding these advances, it is important for physicians, physician assistants, and nurse practitioners to understand the risks and limitations associated with advanced imaging in children and to limit imaging studies that are considered low value, when possible. This technical report provides a summary of imaging strategies for specific conditions where advanced imaging is commonly considered in the emergency department. As an accompaniment to the policy statement, this document provides resources and strategies to optimize advanced imaging, including clinical decision support mechanisms, teleradiology, shared decision-making, and rationale for deferred imaging for patients who will be transferred for definitive care.

Optimizing Advanced Imaging of the Pediatric Patient in the Emergency Department: Policy Statement.

Advanced imaging, including ultrasonography, computed tomography, and magnetic resonance imaging, is an integral component to the evaluation and management of ill and injured children in the emergency department. As with any test or intervention, the benefits and potential impacts on management must be weighed against the risks to ensure that high-value care is being delivered. There are important considerations specific to the pediatric patient related to the ordering and interpretation of advanced imaging. This policy statement provides guidelines for institutions and those who care for children to optimize the use of advanced imaging in the emergency department setting and was coauthored by experts in pediatric and general emergency medicine, pediatric radiology, and pediatric surgery. The intent is to guide decision-making where children may access care.

Optimizing Advanced Imaging of the Pediatric Patient in the Emergency Department: Technical Report.

Advanced diagnostic imaging modalities, including ultrasonography, computed tomography, and magnetic resonance imaging, are key components in the evaluation and management of pediatric patients presenting to the emergency department. Advances in imaging technology have led to the availability of faster and more accurate tools to improve patient care. Notwithstanding these advances, it is important for physicians, physician assistants, and nurse practitioners to understand the risks and limitations associated with advanced imaging in children and to limit imaging studies that are considered low value, when possible. This technical report provides a summary of imaging strategies for specific conditions where advanced imaging is commonly considered in the emergency department. As an accompaniment to the policy statement, this document provides resources and strategies to optimize advanced imaging, including clinical decision support mechanisms, teleradiology, shared decision-making, and rationale for deferred imaging for patients who will be transferred for definitive care.

An extensive analysis of artificial intelligence and segmentation methods transforming cancer recognition in medical imaging.

Recent advancements in computational intelligence, deep learning, and computer-aided detection have had a significant impact on the field of medical imaging. The task of image segmentation, which involves accurately interpreting and identifying the content of an image, has garnered much attention. The main objective of this task is to separate objects from the background, thereby simplifying and enhancing the significance of the image. However, existing methods for image segmentation have their limitations when applied to certain types of images. This survey paper aims to highlight the importance of image segmentation techniques by providing a thorough examination of their advantages and disadvantages. The accurate detection of cancer regions in medical images is crucial for ensuring effective treatment. In this study, we have also extensive analysis of Computer-Aided Diagnosis (CAD) systems for cancer identification, with a focus on recent research advancements. The paper critically assesses various techniques for cancer detection and compares their effectiveness. Convolutional neural networks (CNNs) have attracted particular interest due to their ability to segment and classify medical images in large datasets, thanks to their capacity for self- learning and decision-making.

Types of Evidence Needed to Assess the Clinical Value of Diagnostic Imaging.

AbstractThe evidence underlying the use of advanced diagnostic imaging is based mainly on diagnostic accuracy studies and not on well-designed trials demonstrating improved patient outcomes. This has led to an expansion of low-value and potentially harmful patient care and raises ethical issues around the widespread implementation of tests with incompletely known benefits and harms. Randomized clinical trials are needed to support the safety and effectiveness of imaging tests and should be required for clearance of most new technologies. Large, diverse cohort studies are needed to quantify disease risk associated with many imaging findings, especially incidental findings, to enable evidence-based management. The responsibility to minimize the use of tests with unknown or low value requires engagement of clinicians, medical societies, and the public.

The Evolving Role of Novel Imaging Techniques for Radiotherapy Planning.

The ability to visualise cancer with imaging has been crucial to the evolution of modern radiotherapy (RT) planning and delivery. And as evolving RT technologies deliver increasingly precise treatment, the importance of accurate identification and delineation of disease assumes ever greater significance. However, innovation in imaging technology has matched that seen with RT delivery platforms, and novel imaging techniques are a focus of much research activity. How these imaging modalities may alter and improve the diagnosis and staging of cancer is an important question, but already well served by the literature. What is less clear is how novel imaging techniques may influence and improve practical and technical aspects of RT planning and delivery. In this review, current gold standard approaches to integration of imaging, and potential future applications of bleeding-edge imaging technology into RT planning pathways are explored.

Imaging in pleural Mesothelioma: A review of the 16th International Conference of the International Mesothelioma Interest Group.

Imaging continues to gain a greater role in the assessment and clinical management of patients with mesothelioma. This communication summarizes the oral presentations from the imaging session at the 2023 International Conference of the International Mesothelioma Interest Group (iMig), which was held in Lille, France from June 26 to 28, 2023. Topics at this session included an overview of best practices for clinical imaging of mesothelioma as reported by an iMig consensus panel, emerging imaging techniques for surgical planning, radiologic assessment of malignant pleural effusion, a radiomics-based transfer learning model to predict patient response to treatment, automated assessment of early contrast enhancement, and tumor thickness for response assessment in peritoneal mesothelioma.

Audit and feedback to change diagnostic image ordering practices: A systematic review and meta-analysis.

BACKGROUND: Up to 30% of diagnostic imaging (DI) tests may be unnecessary, leading to increased healthcare costs and the possibility of patient harm. The primary objective of this systematic review was to assess the effect of audit and feedback (AF) interventions directed at healthcare providers on reducing image ordering. The secondary objective was to examine the effect of AF on the appropriateness of DI ordering. METHODS: Studies were identified using MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials and ClinicalTrials.gov registry on December 22nd, 2022. Studies were included if they were randomized control trials (RCTs), targeted healthcare professionals, and studied AF as the sole intervention or as the core component of a multi-faceted intervention. Risk of bias for each study was evaluated using the Cochrane risk of bias tool. Meta-analyses were completed using RevMan software and results were displayed in forest plots. RESULTS: Eleven RCTs enrolling 4311 clinicians or practices were included. AF interventions resulted in 1.5 fewer image test orders per 1000 patients seen than control interventions (95% confidence interval (CI) for the difference -2.6 to -0.4, p-value = 0.009). The effect of AF on appropriateness was not statistically significant, with a 3.2% (95% CI -1.5 to 7.7%, p-value = 0.18) greater likelihood of test orders being considered appropriate with AF vs control interventions. The strength of evidence was rated as moderate for the primary objective but was very low for the appropriateness outcome because of risk of bias, inconsistency in findings, indirectness, and imprecision. CONCLUSION: AF interventions are associated with a modest reduction in total DI ordering with moderate certainty, suggesting some benefit of AF. Individual studies document effects of AF on image order appropriateness ranging from a non-significant trend toward worsening to a highly significant improvement, but the weighted average effect size from the meta-analysis is not statistically significant with very low certainty.

Channel-Specific and Spatial Residual Attention Network for Medical Image Denoising.

Medical image quality is crucial for physicians to ensure accurate diagnosis and therapeutic strategies. However, due to the interference of noise, there are often various types of noise and artifacts in medical images. This not only damages the visual clarity of images, but also reduces the accuracy of information extraction. Considering that the edges of medical images are rich in high-frequency information, to enhance the quality of medical images, a dual attention mechanism, the channel-specific and spatial residual attention network (CSRAN) in the U-Net framework is proposed. The CSRAN seamlessly integrates the U-Net architecture with channel-wise and spatial feature attention (CSAR) modules, as well as low-frequency channel attention modules. Combined with the two modules, the ability of medical image processing to extract high-frequency features is improved, thereby significantly improving the edge effects and clarity of reconstructed images. This model can present better performance in capturing high-frequency information and spatial structures in medical image denoising and super-resolution reconstruction tasks. It cannot only enhance the ability to extract high-frequency features and strengthen its nonlinear representation capability, but also endow strong edge detection capabilities of the model. The experimental results further prove the superiority of CSRAN in medical image denoising and super-resolution reconstruction tasks.

Magnetic Nanoparticles for Biomedical and Imaging Applications.

Magnetic nanoparticles (MNPs) are a class of nanomaterials composed of metals such as cobalt, nickel, and iron with paramagnetic, ferromagnetic, or superparamagnetic properties [...].

On the evaluation of deep learning interpretability methods for medical images under the scope of faithfulness.

BACKGROUND AND OBJECTIVE: Evaluating the interpretability of Deep Learning models is crucial for building trust and gaining insights into their decision-making processes. In this work, we employ class activation map based attribution methods in a setting where only High-Resolution Class Activation Mapping (HiResCAM) is known to produce faithful explanations. The objective is to evaluate the quality of the attribution maps using quantitative metrics and investigate whether faithfulness aligns with the metrics results. METHODS: We fine-tune pre-trained deep learning architectures over four medical image datasets in order to calculate attribution maps. The maps are evaluated on a threefold metrics basis utilizing well-established evaluation scores. RESULTS: Our experimental findings suggest that the Area Over Perturbation Curve (AOPC) and Max-Sensitivity scores favor the HiResCAM maps. On the other hand, the Heatmap Assisted Accuracy Score (HAAS) does not provide insights to our comparison as it evaluates almost all maps as inaccurate. To this purpose we further compare our calculated values against values obtained over a diverse group of models which are trained on non-medical benchmark datasets, to eventually achieve more responsive results. CONCLUSION: This study develops a series of experiments to discuss the connection between faithfulness and quantitative metrics over medical attribution maps. HiResCAM preserves the gradient effect on a pixel level ultimately producing high-resolution, informative and resilient mappings. In turn, this is depicted in the results of AOPC and Max-Sensitivity metrics, successfully identifying the faithful algorithm. In regards to HAAS, our experiments yield that it is sensitive over complex medical patterns, commonly characterized by strong color dependency and multiple attention areas.

The Role of Imaging for Gastrointestinal Bleeding: Consensus Recommendations From the American College of Gastroenterology and Society of Abdominal Radiology.

Gastrointestinal (GI) bleeding is the most common GI diagnosis leading to hospitalization within the United States. Prompt diagnosis and treatment of GI bleeding is critical to improving patient outcomes and reducing high healthcare utilization and costs. Radiologic techniques including computed tomography angiography, catheter angiography, computed tomography enterography, magnetic resonance enterography, nuclear medicine red blood cell scan, and technetium-99m pertechnetate scintigraphy (Meckel scan) are frequently used to evaluate patients with GI bleeding and are complementary to GI endoscopy. However, multiple management guidelines exist which differ in the recommended utilization of these radiologic examinations. This variability can lead to confusion as to how these tests should be used in the evaluation of GI bleeding. In this document, a panel of experts from the American College of Gastroenterology and Society of Abdominal Radiology provide a review of the radiologic examinations used to evaluate for GI bleeding including nomenclature, technique, performance, advantages, and limitations. A comparison of advantages and limitations relative to endoscopic examinations is also included. Finally, consensus statements and recommendations on technical parameters and utilization of radiologic techniques for GI bleeding are provided.