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Liver Neoplasms

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Accurate 3D-dose-based generation of MLC segments for robotic radiotherapy.

Physics in medicine and biology
Radiotherapy treatment planning requires accurate modeling of the delivered patient dose, including radiation scatter effects, multi-leaf collimator (MLC) leaf transmission, interleaf-leakage, etc. In fluence map optimization (FMO), a simple dose mod...

Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Detection and characterization of focal liver lesions (FLLs) is key for optimizing treatment for patients who may have a primary hepatic cancer or metastatic disease to the liver. This is the first study to develop an EUS-based c...

Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning.

Journal of cancer research and clinical oncology
PURPOSE: Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI...

Deep learning based genome analysis and NGS-RNA LL identification with a novel hybrid model.

Bio Systems
The conventional image segmentation techniques have a lot of issues with highest computational cost and low level accuracy for medical image diagnosis and genome analysis. The deep learning based optimization models utilize to predict the liver cance...

Artificial neural network model for preoperative prediction of severe liver failure after hemihepatectomy in patients with hepatocellular carcinoma.

Surgery
BACKGROUND: Posthepatectomy liver failure is a worrisome complication after major hepatectomy for hepatocellular carcinoma and is the leading cause of postoperative mortality. Recommendations for hepatectomy for hepatocellular carcinoma are based on ...

Deep learning and level set approach for liver and tumor segmentation from CT scans.

Journal of applied clinical medical physics
PURPOSE: Segmentation of liver organ and tumors from computed tomography (CT) scans is an important task for hepatic surgical planning. Manual segmentation of liver and tumors is tedious, time-consuming, and biased to the clinician experience. Theref...

Robotic Partial Segment VIII Resection.

Annals of surgical oncology
BACKGROUND:: Robotic partial hepatectomy is an important tool for the treatment of colorectal liver metastases, offering the benefits of a minimally invasive approach with advanced wristed motion, precision, and dexterity. We demonstrate the steps of...

Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges.

Journal of infection and public health
Cancer is a fatal illness often caused by genetic disorder aggregation and a variety of pathological changes. Cancerous cells are abnormal areas often growing in any part of human body that are life-threatening. Cancer also known as tumor must be qui...