[HTML][HTML] Radiomics with artificial intelligence: a practical guide for beginners
Radiomics is a relatively new word for the field of radiology, meaning the extraction of a high
number of quantitative features from medical images. Artificial intelligence (AI) is broadly a …
number of quantitative features from medical images. Artificial intelligence (AI) is broadly a …
Texture analysis of imaging: what radiologists need to know
OBJECTIVE. Radiologic texture is the variation in image intensities within an image and is
an important part of radiomics. The objective of this article is to discuss some parameters …
an important part of radiomics. The objective of this article is to discuss some parameters …
[HTML][HTML] The liver tumor segmentation benchmark (lits)
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark
(LiTS), which was organized in conjunction with the IEEE International Symposium on …
(LiTS), which was organized in conjunction with the IEEE International Symposium on …
Modified U-Net (mU-Net) with incorporation of object-dependent high level features for improved liver and liver-tumor segmentation in CT images
Segmentation of livers and liver tumors is one of the most important steps in radiation
therapy of hepatocellular carcinoma. The segmentation task is often done manually, making …
therapy of hepatocellular carcinoma. The segmentation task is often done manually, making …
[HTML][HTML] RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans
Automatic extraction of liver and tumor from CT volumes is a challenging task due to their
heterogeneous and diffusive shapes. Recently, 2D deep convolutional neural networks …
heterogeneous and diffusive shapes. Recently, 2D deep convolutional neural networks …
[HTML][HTML] Practical utility of liver segmentation methods in clinical surgeries and interventions
Clinical imaging (eg, magnetic resonance imaging and computed tomography) is a crucial
adjunct for clinicians, aiding in the diagnosis of diseases and planning of appropriate …
adjunct for clinicians, aiding in the diagnosis of diseases and planning of appropriate …
Dynamic adaptive residual network for liver CT image segmentation
Due to the gray values of liver and surrounding tissues and organs are resemblance in
abdominal computed tomography (CT) images, it is difficult to accurately determine the …
abdominal computed tomography (CT) images, it is difficult to accurately determine the …
Automated segmentation of tissues using CT and MRI: a systematic review
Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …
body using computed tomography and magnetic resonance imaging has been rapidly …
Thermal ablation of biological tissues in disease treatment: A review of computational models and future directions
Percutaneous thermal ablation has proven to be an effective modality for treating both
benign and malignant tumours in various tissues. Among these modalities, radiofrequency …
benign and malignant tumours in various tissues. Among these modalities, radiofrequency …
Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography
Computed tomography (CT) imaging remains the most utilized modality for liver-related
cancer screening and treatment monitoring purposes. Liver, liver tumor and liver vasculature …
cancer screening and treatment monitoring purposes. Liver, liver tumor and liver vasculature …