AIMC Topic: Image Interpretation, Computer-Assisted

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A fuzzy clustering based color-coded diagram for effective illustration of blood perfusion parameters in contrast-enhanced ultrasound videos.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Early identification and diagnosis of tumors are of great significance to improve the survival rate of patients. Amongst other techniques, contrast-enhanced ultrasound is an important means to help doctors diagnose tumors. D...

Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning.

Radiology
Background Deep learning (DL) algorithms are gaining extensive attention for their excellent performance in image recognition tasks. DL models can automatically make a quantitative assessment of complex medical image characteristics and achieve incre...

Fully Automated Segmentation Algorithm for Hematoma Volumetric Analysis in Spontaneous Intracerebral Hemorrhage.

Stroke
Background and Purpose- Hematoma volume measurements influence prognosis and treatment decisions in patients with spontaneous intracerebral hemorrhage (ICH). The aims of this study are to derive and validate a fully automated segmentation algorithm f...

Deep-UV excitation fluorescence microscopy for detection of lymph node metastasis using deep neural network.

Scientific reports
Deep-UV (DUV) excitation fluorescence microscopy has potential to provide rapid diagnosis with simple technique comparing to conventional histopathology based on hematoxylin and eosin (H&E) staining. We established a fluorescent staining protocol for...

Statistical modeling and knowledge-based segmentation of cerebral artery based on TOF-MRA and MR-T1.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: For cerebrovascular segmentation from time-of-flight (TOF) magnetic resonance angiography (MRA), the focused issues are segmentation accuracy, vascular network coverage ratio, and cerebral artery and vein (CA/CV) separation....

A novel enhanced softmax loss function for brain tumour detection using deep learning.

Journal of neuroscience methods
BACKGROUND AND AIM: In deep learning, the sigmoid function is unsuccessfully used for the multiclass classification of the brain tumour due to its limit of binary classification. This study aims to increase the classification accuracy by reducing the...

Brain pathology identification using computer aided diagnostic tool: A systematic review.

Computer methods and programs in biomedicine
Computer aided diagnostic (CAD) has become a significant tool in expanding patient quality-of-life by reducing human errors in diagnosis. CAD can expedite decision-making on complex clinical data automatically. Since brain diseases can be fatal, rapi...

Using multi-layer perceptron with Laplacian edge detector for bladder cancer diagnosis.

Artificial intelligence in medicine
In this paper, the urinary bladder cancer diagnostic method which is based on Multi-Layer Perceptron and Laplacian edge detector is presented. The aim of this paper is to investigate the implementation possibility of a simpler method (Multi-Layer Per...