An advanced medical application solution comprises several routines and advanced image processing, as well as reading complexity. This article discloses a possible solution for a Medical Imaging Downloader within the use of both CornerstoneJS and Orthanc [1, 2] technologies.

Medical Imaging Downloader for CornerstoneJS and Orthanc
Medical Imaging Downloader for CornerstoneJS and Orthanc
The clinical workflow support is provided by systems such as CornerstoneJS and Orthanc to enable role-based processing of several patient cases.

Introduction

In the last article named “Using CornerstoneJS and Orthanc to Support Deep Learning Projects”, we explain the importance of tools such as CornerstoneJS [3, 4] and Orthanc [1, 2] to support our Artificial Intelligence (AI) algorithms. Briefly, these tools are of chief importance to our projects, allowing us to empower our clinicians to provide us with datasets by interacting with those tools [8]. In the end, the datasets will feed our AI models, providing us with the autonomous outputs that clinicians need [5, 6, 7]. …


Implementing and improving tools to support research about the automated analysis of medical images. Our projects feature several datasets and tools that will be important for our Artificial Intelligence novel methods across Medical Imaging applicability.

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Source: Gomoll Research + Design of the GE Healthcare User Interface (UI) consistency efforts post.

Introduction

Artificial Intelligence (AI) has the potential to alter many application domains fundamentally [5, 6, 7]. …


Nowadays, data acquisition and infrastructure for data processing and predictive capabilities are becoming cheaper and faster for small & low resource organizations. As a result, researchers turn, at an ever-increasing rate, to Machine Learning (ML) and Data Science (DS) to implement better Human-Computer Interaction (HCI) in Health Informatics (HI). In this blog post, we will give you an overview of how researchers are leveraging data, technologies and (cheap & fast) infrastructure to improve the User eXperience (UX) and the decision making quality in HI and what new paradigms in HCI are setting the narrative for future research.

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Radiology Software

This article explores the new paradigms of HCI as a discipline on the development of User Interfaces (UIs) regarding HI, the current and future challenges for researchers, and the various trends, stating its innovations and developments. The implementation of those UIs establishes a direct interaction between clinical information availability and medical process accessibility. Thus, a need for workflow optimization changes the way in which we obtain the information, helping the clinical decision-making process. With the emergence of new information datasets and communication technologies, new opportunities have been created in the design and development of UIs by the application of HCI discipline. As an interdisciplinary field, the HCI theoretical roots enclose many several subjects that are also healthcare supportive. These include computing, ergonomics, cognitive sciences, and psychology. Applying HCI to the clinical domain allows less costly solutions but still presents theoretical and practical challenges. This opportunity has led to an impact in the society due to a change in the clinician’s user profile and the use of new interaction techniques. As suggested in the previous paragraphs, HI will also have an impact on HCI by opening new opportunities for applying HCI. …

About

Francisco Maria Calisto

Human-Computer Interaction and Health Informatics enthusiast. Qualified and experienced at working as Research Fellow & Software Engineer.

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