AIMC Topic: Liver Neoplasms

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Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learning.

Medical image analysis
Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially...

Geometrical features assessment of liver's tumor with application of artificial neural network evolved by imperialist competitive algorithm.

International journal for numerical methods in biomedical engineering
Geometrical features of a cancerous tumor embedded in biological soft tissue, including tumor size and depth, are a necessity in the follow-up procedure and making suitable therapeutic decisions. In this paper, a new socio-politically motivated globa...

Towards cybernetic surgery: robotic and augmented reality-assisted liver segmentectomy.

Langenbeck's archives of surgery
BACKGROUND: Augmented reality (AR) in surgery consists in the fusion of synthetic computer-generated images (3D virtual model) obtained from medical imaging preoperative workup and real-time patient images in order to visualize unapparent anatomical ...

Robotic-assisted thermal ablation of liver tumours.

European radiology
OBJECTIVE: This study aimed to assess the technical success, radiation dose, safety and performance level of liver thermal ablation using a computed tomography (CT)-guided robotic positioning system.

Image-guided microwave thermoablation of hepatic tumours using novel robotic guidance: an early experience.

European radiology
OBJECTIVE: To evaluate and compare novel robotic guidance and manual approaches based on procedural accuracy, procedural time, procedural performance, image quality as well as patient dose during image-guided microwave thermoablation.

Joint sparse coding based spatial pyramid matching for classification of color medical image.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Although color medical images are important in clinical practice, they are usually converted to grayscale for further processing in pattern recognition, resulting in loss of rich color information. The sparse coding based linear spatial pyramid match...

Unraveling risk factors and transcriptomic signatures in liver cancer progression and mortality through machine learning and bioinformatics.

Briefings in functional genomics
Liver cancer (LC) is the second leading cause of cancer-related deaths globally, yet the molecular mechanisms linking its progression with associated risk factors (RFs) remain poorly understood. To address this, we developed an integrative multi-stag...

Discovery of novel diagnostic biomarkers of hepatocellular carcinoma associated with immune infiltration.

Annals of medicine
OBJECTIVE: Diagnosis of hepatocellular carcinoma (HCC) remains challenging for clinicians. Machine learning approaches and big data analyses are viable strategies for identifying HCC diagnostic markers.