AIMC Topic: Liver Neoplasms

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A novel liver cancer diagnosis method based on patient similarity network and DenseGCN.

Scientific reports
Liver cancer is the main malignancy in terms of mortality rate, accurate diagnosis can help the treatment outcome of liver cancer. Patient similarity network is an important information which helps in cancer diagnosis. However, recent works rarely ta...

Comprehensive Clinical Evaluation of a Deep Learning-Accelerated, Single-Breath-Hold Abdominal HASTE at 1.5 T and 3 T.

Academic radiology
To evaluate the clinical performance of a deep learning-accelerated single-breath-hold half-Fourier acquisition single-shot turbo spin echo (HASTE)-sequence for T2-weighted fat-suppressed MRI of the abdomen at 1.5 T and 3 T in comparison to standard ...

Robot-Assisted Right Colectomy with Sequential Wedge Resection of Segments 4 and 5 of The Liver and Cholecystectomy for Colon Cancer with Metastasis to The Liver.

The American surgeon
The liver is the most common place for colon adenocarcinoma metastasis because of portal circulation. The surgical intervention for patients with colon adenocarcinoma with synchronous metastasis to the liver has been debated. Studies have shown that ...

Deep Learning-Based Assessment of Functional Liver Capacity Using Gadoxetic Acid-Enhanced Hepatobiliary Phase MRI.

Korean journal of radiology
OBJECTIVE: We aimed to develop and test a deep learning algorithm (DLA) for fully automated measurement of the volume and signal intensity (SI) of the liver and spleen using gadoxetic acid-enhanced hepatobiliary phase (HBP)-magnetic resonance imaging...

Deep learning for evaluation of microvascular invasion in hepatocellular carcinoma from tumor areas of histology images.

Hepatology international
BACKGROUND: Microvascular invasion (MVI) is essential for the management of hepatocellular carcinoma (HCC). However, MVI is hard to evaluate in patients without sufficient peri-tumoral tissue samples, which account for over a half of HCC patients.

Multimodal Imaging under Artificial Intelligence Algorithm for the Diagnosis of Liver Cancer and Its Relationship with Expressions of EZH2 and p57.

Computational intelligence and neuroscience
OBJECTIVE: It aimed to explore the diagnostic efficacy of multimodal ultrasound images based on mask region with convolutional neural network (M-RCNN) segmentation algorithm for small liver cancer and analyze the expression of zeste gene enhancer hom...

Automatic Segmentation of Magnetic Resonance Images of Severe Patients with Advanced Liver Cancer and the Molecular Mechanism of Emodin-Induced Apoptosis of HepG2 Cells under the Deep Learning.

Journal of healthcare engineering
To improve the accuracy of clinical diagnosis of severe patients with advanced liver cancer and enhance the effect of chemotherapy treatment, the U-Net model was optimized by introducing the batch normalization (BN) layer and the dropout layer, and t...

Artificial intelligence (AI) models for the ultrasonographic diagnosis of liver tumors and comparison of diagnostic accuracies between AI and human experts.

Journal of gastroenterology
BACKGROUND: Ultrasonography (US) is widely used for the diagnosis of liver tumors. However, the accuracy of the diagnosis largely depends on the visual perception of humans. Hence, we aimed to construct artificial intelligence (AI) models for the dia...