Search Tag: deep learning radiology
2025 21 Sep
Breast density influences both cancer risk and interpretive accuracy in mammography, yet routine assessments remain variable across readers. A new open-source approach aims to bring consistency by combining a custom convolutional neural network with an extreme learning machine layer to classify density into BI-RADS categories A–D. Trained on more...Read more
2025 21 Sep
Breast density influences both cancer risk and interpretive accuracy in mammography, yet routine assessments remain variable across readers. A new open-source approach aims to bring consistency by combining a custom convolutional neural network with an extreme learning machine layer to classify density into BI-RADS categories A–D. Trained on more...Read more
2025 21 Sep
Breast density influences both cancer risk and interpretive accuracy in mammography, yet routine assessments remain variable across readers. A new open-source approach aims to bring consistency by combining a custom convolutional neural network with an extreme learning machine layer to classify density into BI-RADS categories A–D. Trained on more...Read more
2025 21 Sep
Breast density influences both cancer risk and interpretive accuracy in mammography, yet routine assessments remain variable across readers. A new open-source approach aims to bring consistency by combining a custom convolutional neural network with an extreme learning machine layer to classify density into BI-RADS categories A–D. Trained on more...Read more
2025 13 Aug
Whole-body imaging plays a critical role in clinical diagnosis, treatment planning and research, but accurate delineation of multiple organs across different modalities remains a challenge. MRI offers superior soft-tissue contrast and avoids ionising radiation, making it suitable for longitudinal studies, yet its segmentation is hindered by variable...Read more
2025 13 Aug
Whole-body imaging plays a critical role in clinical diagnosis, treatment planning and research, but accurate delineation of multiple organs across different modalities remains a challenge. MRI offers superior soft-tissue contrast and avoids ionising radiation, making it suitable for longitudinal studies, yet its segmentation is hindered by variable...Read more
2025 30 May
Artificial intelligence (AI) and deep learning have brought transformative potential to radiology, supporting diagnostics, workflow optimisation and triage. However, concerns regarding algorithmic bias have surfaced as these models are deployed in clinical settings. These biases, often embedded in training data, can lead to performance disparities...Read more
2025 30 May
Artificial intelligence (AI) and deep learning have brought transformative potential to radiology, supporting diagnostics, workflow optimisation and triage. However, concerns regarding algorithmic bias have surfaced as these models are deployed in clinical settings. These biases, often embedded in training data, can lead to performance disparities...Read more
2025 30 May
Artificial intelligence (AI) and deep learning have brought transformative potential to radiology, supporting diagnostics, workflow optimisation and triage. However, concerns regarding algorithmic bias have surfaced as these models are deployed in clinical settings. These biases, often embedded in training data, can lead to performance disparities...Read more
2024 22 Jul
Autosomal dominant polycystic kidney disease (ADPKD) is a hereditary condition that significantly impacts kidney function, affecting approximately 500,000 individuals in the United States and 12.4 million worldwide. This disease often involves multiple organs, including the liver, leading to polycystic liver disease (PLD). PLD is characterised...Read more