IEEE journal of biomedical and health informatics
Jun 1, 2025
This paper introduces an innovative approach for automated polyp segmentation in colonoscopy images, deploying an enhanced Pix2Pix Generative Adversarial Network (GAN) equipped with an integrated attention mechanism in the discriminator. Addressing p...
BMC medical informatics and decision making
May 30, 2025
PURPOSE: This study aims to develop a deep learning framework that leverages modality imputation and subregion segmentation to improve grading accuracy in high-grade gliomas.
Breast cancer diagnosis remains a crucial challenge in medical research, necessitating accurate and automated detection methods. This study introduces an advanced deep learning framework for histopathological image classification, integrating AlexNet...
BACKGROUND: Diffusion-weighted imaging with higher b-value improves detection rate for prostate cancer lesions. However, obtaining high b-value DWI requires more advanced hardware and software configuration. Here we use a novel deep learning network,...
Liver cancer, especially hepatocellular carcinoma (HCC), remains one of the most fatal cancers globally, emphasizing the critical need for accurate tumor segmentation to enable timely diagnosis and effective treatment planning. Traditional imaging te...
The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment strategies for each ...
Breast cancer represents a significant global health challenge, which makes it essential to detect breast cancer early and accurately to improve patient prognosis and reduce mortality rates. However, traditional diagnostic processes relying on manual...
OBJECTIVE: Development of a deep learning model for accurate preoperative identification of glioblastoma and solitary brain metastases by combining multi-centre and multi-sequence magnetic resonance images and comparison of the performance of differe...
BACKGROUND: Basal cell carcinoma (BCC) is the most common skin cancer, placing a significant burden on healthcare systems globally. Developing high-precision automated diagnostics requires large annotated datasets, which are costly and difficult to o...
Studies in health technology and informatics
May 15, 2025
Currently, dermatologists need to check numerous image reports (high resolution) for diagnosing skin conditions, and Machine Learning (ML) models can help with this tedious task. However, current ML models usually work best with high-quality images i...
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