AIMC Topic: Liver Neoplasms

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Leverage prior texture information in deep learning-based liver tumor segmentation: A plug-and-play Texture-Based Auto Pseudo Label module.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Segmenting the liver and tumor regions using CT scans is crucial for the subsequent treatment in clinical practice and radiotherapy. Recently, liver and tumor segmentation techniques based on U-Net have gained popularity. However, there are numerous ...

[Possible Radiation Dose Reduction in Abdominal Plain CT Using Deep Learning Reconstruction].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: The purposes of this study were to evaluate the low-contrast detectability of CT images assuming hepatocellular carcinoma and to determine whether dose reduction in abdominal plain CT imaging is possible.

Iodine maps derived from sparse-view kV-switching dual-energy CT equipped with a deep learning reconstruction for diagnosis of hepatocellular carcinoma.

Scientific reports
Deep learning-based spectral CT imaging (DL-SCTI) is a novel type of fast kilovolt-switching dual-energy CT equipped with a cascaded deep-learning reconstruction which completes the views missing in the sinogram space and improves the image quality i...

Hepatocellular Carcinoma Recognition from Ultrasound Images Using Combinations of Conventional and Deep Learning Techniques.

Sensors (Basel, Switzerland)
Hepatocellular Carcinoma (HCC) is the most frequent malignant liver tumor and the third cause of cancer-related deaths worldwide. For many years, the golden standard for HCC diagnosis has been the needle biopsy, which is invasive and carries risks. C...

Perioperative outcomes of robot-assisted versus laparoscopic liver resection for cavernous hemangioma: a propensity score matching study.

Surgical endoscopy
BACKGROUND: Minimally invasive techniques have increasingly been adopted for liver resection. This study aimed to compare the perioperative outcomes of robot-assisted liver resection (RALR) with laparoscopic liver resection (LLR) for liver cavernous ...

Artificial intelligence in liver cancers: Decoding the impact of machine learning models in clinical diagnosis of primary liver cancers and liver cancer metastases.

Pharmacological research
Liver cancers are the fourth leading cause of cancer-related mortality worldwide. In the past decade, breakthroughs in the field of artificial intelligence (AI) have inspired development of algorithms in the cancer setting. A growing body of recent s...

A 3D Tumor-Mimicking In Vitro Drug Release Model of Locoregional Chemoembolization Using Deep Learning-Based Quantitative Analyses.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Primary liver cancer, with the predominant form as hepatocellular carcinoma (HCC), remains a worldwide health problem due to its aggressive and lethal nature. Transarterial chemoembolization, the first-line treatment option of unresectable HCC that e...

Deep learning nomogram based on Gd-EOB-DTPA MRI for predicting early recurrence in hepatocellular carcinoma after hepatectomy.

European radiology
OBJECTIVES: The accurate prediction of post-hepatectomy early recurrence in patients with hepatocellular carcinoma (HCC) is crucial for decision-making regarding postoperative adjuvant treatment and monitoring. We aimed to explore the feasibility of ...

Implementing deep learning models for the classification of Echinococcus multilocularis infection in human liver tissue.

Parasites & vectors
BACKGROUND: The histological diagnosis of alveolar echinococcosis can be challenging. Decision support models based on deep learning (DL) are increasingly used to aid pathologists, but data on the histology of tissue-invasive parasitic infections are...

Synthetic-to-real domain adaptation with deep learning for fitting the intravoxel incoherent motion model of diffusion-weighted imaging.

Medical physics
BACKGROUND: Intravoxel incoherent motion (IVIM) is a type of diffusion-weighted imaging (DWI), and IVIM model parameters (water molecule diffusion rate D , pseudo-diffusion coefficient D , and tissue perfusion fraction F ) have been widely used in th...