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The purpose of this paper is to highlight the relation between radiology and sustainable development with emphasis on the UK and European countries, and to spotlight its possible application in the developing countries.

This is a review paper where data about sustainable development and radiology are collected from selected journals, websites, articles and conferences, e.g. Royal College of Radiology, European Society of Radiology, World Health Organization and other different radiology societies.

Adoption of sustainable diagnostic radiology by many countries in Europe and the UK helps to provide imaging services efficiently and effectively, with simultaneous preservation of the natural resources, patient health and environment much better than before. The developing and underdeveloped countries should follow this knowledge hoping to reach the same goals.

Limiting the use of radiologic examinations, guide the clinicians to use clinical skills before rushing to radiology examinations will save money, preserve equipment and protect patients from possible radiation hazards. The use of teleradiology will indirectly reduce global warming, and will deliver medical services to poor countries.

Improving the health of people of poor countries will improve their socioeconomic level.

This paper focuses on the value of applying sustainable development in radiology not only in general medicine.

Illustrates a case story detailing the customer‐vendor co‐operation in a project concerning the beta test of hardware and software at a radiology department. A qualitative analysis of the project has unveiled that contextual conditions like the nature of the technology, the organizational structure at both the customer and the vendor side, the development strategy, and the project organization were very important forces during the project. Technologically, the project was more complex than usually was seen at the hospital because it concerned both biomedical and administrative aspects. Conflicting interests in particular on the part of the customer side as well as between the customer and the vendor affected the course of the project. Methodologically, the project lacked a proper strategy for the co‐operative process. There was no formalized project organization which otherwise could have provided different conditions for the project.

Meeting the patients' requirements as customers of the health care sector is crucially important as a social responsibility. According to the resource constraints, only an efficient utilisation of health services can provide that purpose. This study aims to develop a quantitative assessment framework for radiology centres as a vital section in healthcare to translate the patients' requirements into service quality specifications. This would help to achieve quality improvement by emphasising the voice of customers.

A literature review is conducted to specify the service quality criteria and the patients' requirements related to healthcare and hospitals. Based on the experts' opinions, these criteria and requirements are later customised for the radiology centres. Moreover, the requirements are categorised into five dimensions of SERVQUAL. The interrelations between service elements are also determined through expert group consensus using Pearson correlation. Afterwards, by applying the QFD method, the relations between the requirements and criteria are explored. Additionally, a customer satisfaction survey is executed in Tehran public hospitals to prioritise these requirements and provide an importance-satisfaction analysis.

Based on the result of the case study, service elements are prioritised for improvement, and practical suggestions are provided using the Delphi technique for quality improvement. In addition, a cause-and-effect diagram is presented to highlight the improvement area and provide enhancement suggestions.

This study is the first empirical attempt to benefit from the VOC in evaluating and enhancing the quality of service delivered to radiology patients. In doing so, the study applies a hybrid approach of QFD and SERVQUAL as well as other tools to highlight the improvement area and provide enhancement suggestions. The findings can be readily used by the practitioners.

The healthcare industry is facing several challenges such as the reduction of costs and quality improvement of the provided services. Engineering studies could be very useful in supporting organizational and management processes. Healthcare service efficiency depends on a strong collaboration between clinical and engineering experts, especially when it comes to analyzing the system and its constraints in detail and subsequently, when it comes to deciding on the reengineering of some key activities. The purpose of this paper is to propose a case study showing how a mix of representation tools allow a Manager of a Radiology Department to solve some human and technological resource re‐organizational issues, which have to be faced due to the introduction of a new technology and a new portfolio of services.

In order to simulate the activities within the radiology department and examine the relationship between human and technological resources, different visual diagrammatic language (VDL) techniques have been implemented to get knowledge about the heterogeneous factors related to the healthcare service delivery. In particular, flow charts, IDEF0 diagrams and Petri nets have been integrated each other with success as a modelisation tools.

The simulation study performed through the application of the aforementioned VDL techniques suggests the opportunity of re‐organizing the nurse activities within the radiology department.

The re‐organization of a healthcare service and in particular of a radiology department by means of joint flow charts, IDEF0 diagrams and Petri nets is a poorly investigated topic in literature. This paper demonstrates how flow charts and IDEF0 can help people working within the department to understand the weak points of their organization and constitute an efficient base of knowledge for the implementation of a Petri net aimed at improving the departmental performance.

Many international radiology societies, including American College of Radiologists (ACR), have established guidelines for optimum forms and contents of medical imaging reports to ensure high quality and to guarantee the satisfaction of both the referring physician and the patient. Therefore, this study aims to analyze the criteria of magnetic resonance imaging (MRI) reports in Jordan according to the standards of the ACR.

This cross-sectional study was conducted in early January 2021 for two weeks. An invitation letter was sent to 85 MRI centers of various health-care sectors in Jordan to participate in the study. Each invitee was requested to send at least ten different MRI reports. The study used a questionnaire containing the checklist of the latest edition 2020 of ACR’s practice parameter to communicate the diagnostic imaging results and the demographic information of the participating MRI centers. Seven basic elements were assessed for content-related quality of MRI reports, which are administrative data, patient demographics, clinical history, imaging procedures, clinical symptoms, imaging observations and impressions. Statistical analyses were used to evaluate the data.

Forty-one MRI centers participated in the study with 386 different MRI exam reports. The majority (92%) of the reports were computer-generated. Free texted unstructured reports and head-structured reports had an almost equal percentage of around 40%. Exam and radiologist demography as well as exam findings criteria were 100% available in all reports. The percentage of exam conclusion, and exam description and techniques were 2% and 4.9%, respectively (N = 368). There was a positive association between computer-generated reports and the presence of picture archiving and communication systems (PACS)/health information systems r = 0.443.

Structured and free text unstructured reporting were the common types of MRI exam reports in Jordan. Handwriting exam reporting existed in few MRI centers, particularly in those that had no PACS and radiology information systems.

To provide insights into the current supply chain for original equipment manufacturers (OEM) in the radiology diagnostic imaging equipment business. As is common in many manufacturing and service firms, the rationale of bridging suppliers of OEMs is the ability to leverage technology, software, and accessories pertaining to the various pieces of equipment.

Several models of e‐procurement and e‐commerce related to the health care industry are presented.

Although the radiology capital equipment market presents numerous idiosyncrasies that must be addressed to successfully implement an e‐business strategy effectively, incredible opportunities exist all along the supply chain for e‐business strategies to both eliminate costs and acquire strategic initiatives. Those firms that most successfully listen to their customers and address the barriers to efficiency (B2E) will help move the industry toward more effective utilization of the benefits e‐business can create and also obtain first mover advantages.

Although the efficiencies that e‐business provides are extremely important in the radiology capital equipment market, the main value of e‐business in this industry of high‐priced and relatively infrequently purchased equipment may well be the value‐added benefits the technology brings to its customers, as illustrated in the modeling process. The OEMs that eventually market their finished product directly to hospital and imaging centers via a direct sales force can best take advantage of the connectivity and accessibility of e‐commerce.

The purpose of this paper is to improve the mammography and ultrasound screening processes to increase the healthcare system quality and patients’ pleasantness while decreasing costs.

The data storage system is very insufficient so that data are collected from hospital staff and by personal observations. A lean management tool, value stream mapping is used to see the general view of the radiology department with its problems at a glance. Data and the map are used as a guide to conduct a quality house to make a prioritization between the problems, to decide which one to solve first, of patients at the hospital.

Problems of the radiology department related to mammography and ultrasound and suggestions to these problems according to the quality house conducted.

The paper consequently focuses on the value creation process and on how to revisit managing for quality in the systems perspective.

The purpose of this study is to investigate and demonstrate the advancements achieved in the field of chest X-ray image captioning through the utilization of dynamic convolutional encoder–decoder networks (DyCNN). Typical convolutional neural networks (CNNs) are unable to capture both local and global contextual information effectively and apply a uniform operation to all pixels in an image. To address this, we propose an innovative approach that integrates a dynamic convolution operation at the encoder stage, improving image encoding quality and disease detection. In addition, a decoder based on the gated recurrent unit (GRU) is used for language modeling, and an attention network is incorporated to enhance consistency. This novel combination allows for improved feature extraction, mimicking the expertise of radiologists by selectively focusing on important areas and producing coherent captions with valuable clinical information.

In this study, we have presented a new report generation approach that utilizes dynamic convolution applied Resnet-101 (DyCNN) as an encoder (Verelst and Tuytelaars, 2019) and GRU as a decoder (Dey and Salemt, 2017; Pan et al., 2020), along with an attention network (see Figure 1). This integration innovatively extends the capabilities of image encoding and sequential caption generation, representing a shift from conventional CNN architectures. With its ability to dynamically adapt receptive fields, the DyCNN excels at capturing features of varying scales within the CXR images. This dynamic adaptability significantly enhances the granularity of feature extraction, enabling precise representation of localized abnormalities and structural intricacies. By incorporating this flexibility into the encoding process, our model can distil meaningful and contextually rich features from the radiographic data. While the attention mechanism enables the model to selectively focus on different regions of the image during caption generation. The attention mechanism enhances the report generation process by allowing the model to assign different importance weights to different regions of the image, mimicking human perception. In parallel, the GRU-based decoder adds a critical dimension to the process by ensuring a smooth, sequential generation of captions.

The findings of this study highlight the significant advancements achieved in chest X-ray image captioning through the utilization of dynamic convolutional encoder–decoder networks (DyCNN). Experiments conducted using the IU-Chest X-ray datasets showed that the proposed model outperformed other state-of-the-art approaches. The model achieved notable scores, including a BLEU_1 score of 0.591, a BLEU_2 score of 0.347, a BLEU_3 score of 0.277 and a BLEU_4 score of 0.155. These results highlight the efficiency and efficacy of the model in producing precise radiology reports, enhancing image interpretation and clinical decision-making.

This work is the first of its kind, which employs DyCNN as an encoder to extract features from CXR images. In addition, GRU as the decoder for language modeling was utilized and the attention mechanisms into the model architecture were incorporated.

The purpose of this paper is to provide a framework for analysing and modelling detailed workflow of image‐guided interventions to facilitate simulation and the re‐engineering process for the development of new procedures in multi‐modal imaging environments.

The methodology presented includes a literature review on workflow simulation in surgery, focussing on radiology environments, an assessment of simulation tools, a data gathering and management framework and research on methods for conceptual modelling of the processes.

The literature review reveals that few authors attempted to analyse the phases within image‐guided interventions, and those that did, only did so partially. The framework developed for this work intends to fill the gap found in the survey. It allows the maintenance and management of large amounts of data, one of the most critical factors when modelling detailed workflow. In addition, selecting the appropriate simulation software plays an important role, saving time in later stages of the project.

The framework presented for endovascular interventions can be extended to other types of image‐guided interventions. Moreover, modelling the workflow processes in a modular way facilitates the re‐engineering process when integrating different imaging modalities during the same procedure.

The use of radiology in industry has been used in welding and casting technology for many years for the non‐destructive examination of defects.