Search Tag: deep learning
2024 16 Sep
Prostate cancer is the second most common cancer among men worldwide, making early detection crucial for reducing morbidity and mortality rates. One of the key tools for identifying clinically significant prostate cancer (csPCa) is multiparametric magnetic resonance imaging (mpMRI). However, the process of detecting prostate cancer through mpMRI...Read more
2024 16 Sep
Lung cancer remains a significant cause of mortality, and early detection is essential to improving patient outcomes. The advent of lung cancer screening trials like the National Lung Screening Trial (NLST) and the Danish Lung Cancer Screening Trial (DLCST) has highlighted the potential of low-dose computed tomography (CT) scans in detecting lung...Read more
2024 08 Sep
Motion artefacts during medical imaging, particularly in craniocervical angiography, pose significant challenges to accurate diagnosis and treatment planning. Digital Subtraction Angiography (DSA), a commonly used technique, suffers from image degradation caused by patient movement. This leads to increased radiation exposure and extended procedure...Read more
2024 19 Jul
Cardiovascular diseases (CVD) are the leading cause of mortality and morbidity in women worldwide. Traditional risk scores such as the Framingham score often fail to accurately assess the risk in women, leading to missed opportunities for early diagnosis and prevention. Recently, breast arterial calcifications (BAC), visible on routine mammograms,...Read more
2024 19 Jul
Cardiovascular diseases (CVD) are the leading cause of mortality and morbidity in women worldwide. Traditional risk scores such as the Framingham score often fail to accurately assess the risk in women, leading to missed opportunities for early diagnosis and prevention. Recently, breast arterial calcifications (BAC), visible on routine mammograms,...Read more
2024 10 Jul
Early detection of liver metastases is critical for effective cancer management and long-term prognosis. Computed Tomography (CT) scans play a pivotal role in this process, relying on various reconstruction algorithms to convert raw data into usable images. The most common technique, Adaptive Statistical Iterative Reconstruction-V (ASiR-V), reduces...Read more
2024 10 Jul
Early detection of liver metastases is critical for effective cancer management and long-term prognosis. Computed Tomography (CT) scans play a pivotal role in this process, relying on various reconstruction algorithms to convert raw data into usable images. The most common technique, Adaptive Statistical Iterative Reconstruction-V (ASiR-V), reduces...Read more
2024 13 Jun
Alzheimer's disease is characterised by the buildup of amyloid-β plaques in the brain. Amyloid PET imaging is crucial for diagnosis and treatment planning. While visual interpretation is common, it has limitations. Quantitative analysis, despite being more accurate, is operator-dependent. As disease-modifying treatments emerge, there's a growing...Read more
2024 29 May
While multiparametric magnetic resonance imaging (mpMRI) has become integral in prostate cancer (PCa) diagnosis, there's a debate regarding the inclusion of dynamic contrast-enhanced (DCE) sequences in future PI-RADS iterations due to questionable benefits. To address time constraints, biparametric (bp) protocols, omitting DCE sequences, have...Read more
2024 16 May
Treatment Effect Estimation (TEE) is essential in healthcare to evaluate the impact of treatment strategies on outcomes. While Randomized Clinical Trials (RCTs) are the gold standard, they are costly and time-consuming. Observational data, like medical claims, offer a complementary approach. Neural Network (NN) methods, especially Transformer-based...Read more
2024 16 May
The widespread use of modern imaging has led to increased detection of small renal masses (SRMs), but earlier interventions have not reduced renal cancer-specific mortality rates, as many of these lesions are benign or indolent. Revised guidelines suggest using a size cutoff of 3 cm for T1a stage renal cell carcinoma, highlighting the importance...Read more
2024 07 May
In the pursuit of automating the detection and segmentation of intracranial aneurysms (IAs), a recent study published in European Radiology aimed to address the challenge of automating the segmentation and detection of IAs using deep learning techniques, specifically focusing on magnetic resonance T1 images. Through a retrospective diagnostic...Read more
2024 07 May
In the pursuit of automating the detection and segmentation of intracranial aneurysms (IAs), a recent study published in European Radiology aimed to address the challenge of automating the segmentation and detection of IAs using deep learning techniques, specifically focusing on magnetic resonance T1 images. Through a retrospective diagnostic...Read more
2024 24 Apr
Deep learning (DL) models have shown promise in automating tasks like bone age prediction, yet concerns exist regarding their readiness in medicine, particularly in radiology, due to their limited robustness to common clinical image variations. A recent study published in Radiology: Artificial Intelligence assessed the robustness of the winning...Read more
2024 24 Apr
Deep learning (DL) models have shown promise in automating tasks like bone age prediction, yet concerns exist regarding their readiness in medicine, particularly in radiology, due to their limited robustness to common clinical image variations. A recent study published in Radiology: Artificial Intelligence assessed the robustness of the winning...Read more
2024 17 Apr
In vivo ophthalmic imaging offers insight into individual cell status, but noise reduces contrast, prolonging acquisition time and risking artefacts. Adaptive optics optical coherence tomography (AO-OCT) enables high-resolution retinal imaging but suffers from speckle noise, hindering cellular visualisation. Current methods require averaging multiple...Read more
2024 17 Apr
In vivo ophthalmic imaging offers insight into individual cell status, but noise reduces contrast, prolonging acquisition time and risking artefacts. Adaptive optics optical coherence tomography (AO-OCT) enables high-resolution retinal imaging but suffers from speckle noise, hindering cellular visualisation. Current methods require averaging multiple...Read more
2024 25 Mar
As of January 2023, Finland's public healthcare sector has restructured its wellbeing services counties, including Northern Ostrobothnia, under stringent financial limits. Authors reported in the European Journal of Radiology their experience in their hospital, the largest in this region serving 416,000 residents, faces challenges in optimising...Read more
2024 25 Mar
As of January 2023, Finland's public healthcare sector has restructured its wellbeing services counties, including Northern Ostrobothnia, under stringent financial limits. Authors reported in the European Journal of Radiology their experience in their hospital, the largest in this region serving 416,000 residents, faces challenges in optimising...Read more
2024 25 Mar
As of January 2023, Finland's public healthcare sector has restructured its wellbeing services counties, including Northern Ostrobothnia, under stringent financial limits. Authors reported in the European Journal of Radiology their experience in their hospital, the largest in this region serving 416,000 residents, faces challenges in optimising...Read more
2024 19 Mar
The global demand for imaging tests to assess cancer is increasing, but there's a shortage of imaging specialists, particularly in low and middle-income countries. This leads to delays in scan reporting and patient management. Artificial intelligence (AI) using deep neural networks (DNNs) could help handle high scan volumes while maintaining diagnostic...Read more
2024 19 Mar
The global demand for imaging tests to assess cancer is increasing, but there's a shortage of imaging specialists, particularly in low and middle-income countries. This leads to delays in scan reporting and patient management. Artificial intelligence (AI) using deep neural networks (DNNs) could help handle high scan volumes while maintaining diagnostic...Read more
2024 18 Mar
When newborns take their first breath, a complex series of physiological adjustments unfold: their lungs inflate, blood vessels expand, and the entire circulatory system adapts to the new environment. However, this transition doesn't always proceed smoothly. In cases of pulmonary hypertension, particularly prevalent among sick or premature newborns,...Read more
2024 06 Mar
Deep learning (DL) has become important in healthcare for its role in early diagnosis, treatment identification, and patient outcome predictions. However, due to varied medical practices and inconsistent data collection, DL may worsen biases and distort estimates. For instance, sampling bias challenges the effectiveness and applicability of statistical...Read more
2024 08 Feb
A study published in Radiology dwells into the efficacy of a sophisticated deep learning model in accurately predicting short-term subsequent fractures in patients who have recently experienced a hip fracture. This innovative approach utilises digitally reconstructed radiographs obtained from three-dimensional hip CT scans, demonstrating remarkable...Read more
2024 08 Feb
A study published in Radiology dwells into the efficacy of a sophisticated deep learning model in accurately predicting short-term subsequent fractures in patients who have recently experienced a hip fracture. This innovative approach utilises digitally reconstructed radiographs obtained from three-dimensional hip CT scans, demonstrating remarkable...Read more
2024 07 Feb
A groundbreaking study has introduced a pioneering method to predict lymph node metastasis (LNM) in patients with non-functional pancreatic neuroendocrine tumours (NF-PanNETs), aiding in tailored treatment strategies and enhancing patient outcomes. Recently published in eClinicalMedicine, the research team from the University of Tsukuba harnessed...Read more
2024 07 Feb
A groundbreaking study has introduced a pioneering method to predict lymph node metastasis (LNM) in patients with non-functional pancreatic neuroendocrine tumours (NF-PanNETs), aiding in tailored treatment strategies and enhancing patient outcomes. Recently published in eClinicalMedicine, the research team from the University of Tsukuba harnessed...Read more
2023 08 Nov
The 2023 Alexander R. Margulis Award for the best original scientific article published in Radiology has been awarded to researchers of the article “Pancreatic Cancer Detection on CT Scans with Deep Learning: A Nationwide Population-based Study”. The team created an AI tool and trained it by analysing hundreds of contrast-enhanced CT studies...Read more
2023 09 May
Imalogix, an industry leader in deep learning AI for imaging, announced that world renowned radiology leader and clinical researcher Dr. Ehsan Samei has joined the Imalogix team as its Chief Scientific Advisor. Dr. Ehsan Samei, PhD, DABR, FAAPM, FSPIE, FAIMBE, FIOMP, FACR is the Reed and Martha Rice Distinguished Professor of Radiology at Duke...Read more