Search Tag: Deep Learning
2025 10 Jan
Uterine fibroids are a prevalent gynaecological condition that can severely impact the quality of life, often requiring medical intervention. High-Intensity Focused Ultrasound (HIFU) has gained popularity as a non-invasive treatment due to its minimal recovery time and reduced risk compared to surgical options. However, not all patients respond...Read more
2024 09 Dec
Hypopharyngeal Squamous Cell Carcinoma (HSCC) is a particularly aggressive form of head and neck cancer, often characterised by late-stage diagnosis, high rates of recurrence and poor survival outcomes. One critical factor influencing the prognosis of HSCC is lymphovascular invasion (LVI), which occurs when cancer cells infiltrate lymphatic or...Read more
2024 09 Dec
Accurately identifying and treating acute vertebral compression fractures (VCFs) are crucial due to their significant impact on patient mobility and overall quality of life. These injuries, if undetected or improperly treated, can lead to chronic pain, reduced mobility and further complications such as spinal deformities. Traditional diagnostic...Read more
2024 03 Dec
Radiological imaging is a crucial tool for monitoring disease progression and evaluating the effectiveness of treatments over time. By capturing images at different time points, clinicians gain critical insights into changes such as tumour growth, lesion development or responses to therapy. However, comparing these images poses significant challenges...Read more
2024 11 Nov
AI-powered technology continues to reshape healthcare, with the latest innovation aiming to address a critical concern: medication errors. Researchers at the University of Washington have developed an AI-enabled wearable camera capable of detecting potential medication errors with 99% accuracy. This system offers a proactive solution to improve...Read more
2024 10 Nov
Breast cancer remains a significant threat, particularly among high-risk women who benefit from supplemental screening methods such as magnetic resonance imaging (MRI). However, even with advanced imaging, certain malignancies are not detected until they have progressed. Recent advancements in artificial intelligence (AI) offer new possibilities...Read more
2024 10 Nov
Spinal cord injury (SCI) diagnosis and treatment can be challenging due to the complexities of accurately identifying and measuring lesions, which vary in size, location and intensity across patients. Traditional manual segmentation methods are often time-consuming, variable across raters and impractical for large studies or clinical trials. Addressing...Read more
2024 10 Nov
Autosomal dominant polycystic kidney disease (ADPKD) is a genetic disorder characterised by the progressive formation of renal cysts, which ultimately impair kidney function. Traditionally, imaging techniques such as magnetic resonance imaging (MRI) have been employed to evaluate cystic burden. Still, manual segmentation is time-consuming and...Read more
2024 03 Nov
Stroke remains a leading cause of death and long-term disability globally. Rapid and accurate diagnosis is essential for guiding treatment decisions and improving patient outcomes. Computed tomography (CT) imaging, particularly CT angiography (CTA), plays a critical role in evaluating stroke patients by identifying cerebral vessel occlusions....Read more
2024 27 Oct
Cerebral aneurysms are a significant health concern due to their potential to cause non-traumatic subarachnoid haemorrhages, leading to high mortality and long-term disabilities. Early detection is crucial for timely intervention and improved outcomes. While digital subtraction angiography (DSA) is the gold standard for identifying aneurysms,...Read more
2024 21 Oct
Coronary artery calcium (CAC) scoring is an essential method of assessing cardiovascular risk. Traditionally, it has been performed manually, which is time-consuming and error-prone. This is especially true at the segment level, where detailed analysis of individual coronary segments is needed. However, advancements in deep learning have opened...Read more
2024 20 Oct
The increasing use of medical imaging in modern healthcare, particularly for diagnosing conditions such as vascular malformations and acute ischemic strokes, has brought forth the critical issue of patient data privacy. Computed tomography angiography (CTA) is a vital tool for diagnosing vascular issues, but its detailed facial features in head...Read more
2024 01 Oct
The inner ear's intricate three-dimensional anatomy presents substantial challenges for diagnosis and surgical planning, requiring precise imaging to navigate its complex structures. Traditional manual segmentation of inner ear structures from computed tomography (CT) scans is time-consuming and can introduce variability due to human error. With...Read more
2024 01 Sep
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterised by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. These pathological changes begin decades before the appearance of clinical symptoms, making early detection critical for potential intervention. Amyloid PET imaging has emerged as a...Read more
2024 29 May
Microwave lung ablation (MWA) is a method for removing lung tumours with low risk and cost compared to surgery. However, it faces challenges like incomplete tumour removal due to difficulty in achieving sufficient margins. Existing methods for planning MWA based on vendor models often result in discrepancies between planned and actual outcomes....Read more
2024 21 May
Machine learning has significantly advanced various industries, particularly in healthcare, where deep learning is revolutionising drug discovery, early diagnosis, medical imaging, and personalised treatments. However, these advancements come with challenges, notably issues of interpretability, data availability, and inherent biases. Bias in machine...Read more
2024 21 May
Machine learning has significantly advanced various industries, particularly in healthcare, where deep learning is revolutionising drug discovery, early diagnosis, medical imaging, and personalised treatments. However, these advancements come with challenges, notably issues of interpretability, data availability, and inherent biases. Bias in machine...Read more
2024 09 Apr
The evolution of computing power has revolutionized the field of medical imaging, particularly in the realm of computed tomography (CT). One of the significant milestones in this evolution has been the introduction of iterative reconstruction methods, aimed at reducing image noise and radiation dose in CT scans. Initially, these methods were combined...Read more
2024 09 Apr
The evolution of computing power has revolutionized the field of medical imaging, particularly in the realm of computed tomography (CT). One of the significant milestones in this evolution has been the introduction of iterative reconstruction methods, aimed at reducing image noise and radiation dose in CT scans. Initially, these methods were combined...Read more
2024 01 Feb
Research into the use of AI methods to enhance MRI scan acquisition, particularly in musculoskeletal radiology, has seen significant advancement since 2016. While initial studies show promise in improving image resolution and speeding up imaging processes, questions remain about the reliability of AI-generated images for routine clinical use. Establishing...Read more
2024 01 Feb
Research into the use of AI methods to enhance MRI scan acquisition, particularly in musculoskeletal radiology, has seen significant advancement since 2016. While initial studies show promise in improving image resolution and speeding up imaging processes, questions remain about the reliability of AI-generated images for routine clinical use. Establishing...Read more
2022 13 Jan
Fluid-attenuation inversion recovery (FLAIR) is a commonly-used sequence for estimating the age of an acute ischemic stroke. Timing information is essential for considering intravenous tissue plasminogen activator (tPA) to treat ischaemic stroke. One critical advantage synthetic FLAIR have over conventional FLAIR is its potential to reduce scan times in...Read more
2020 10 Feb
A new study published in the journal Radiology describes the feasibility of using a deep learning model to accurately assess radiographic features of hip osteoarthritis. The AI model's performance even rivalled the accuracy of trained radiologists , according to researchers. You might also like: White Paper...Read more
2017 07 Mar
Royal Philips and LabPON, the first clinical laboratory to transition to 100% histopathology digital diagnosis, has announced its plans to create a digital database of massive aggregated sets of annotated pathology images and big data utilizing Philips IntelliSite Pathology Solution 1 . The database will provide pathologists with a wealth of clinical...Read more