Publications by authors named "Arjmandi N"
Article Synopsis
- The study assessed the effectiveness of deep-learning-based auto-contouring in delineating clinical target volumes (CTV) and organs at risk (OARs) for prostate cancer radiotherapy, comparing it to traditional manual methods.
- It involved analyzing 28 planning CT volumes with three contour types: original, auto-segmented, and expert-defined, examining dosimetric characteristics through various metrics like dose-volume histograms and homogeneity indices.
- Results showed automated contours had smaller geometric differences from manual contours than variations between different experts, and the automated process also significantly reduced contouring time while maintaining comparable dosimetric accuracy.
Introduction: No study has yet investigated the minimum amount of data required for deep learning-based liver contouring. Therefore, this study aimed to investigate the feasibility of automated liver contouring using limited data.
Methods: Radiotherapy planning Computed tomography (CT) images were subjected to various preprocessing methods, such as denoising and windowing.
Article Synopsis
- Manual contouring of the prostate in CT imaging is difficult due to low tissue contrast and variability among observers, making automated methods advantageous.
- This study explored a hybrid CNN-ViT model for contouring multiple male pelvic organs in CT images, using data from 104 localized prostate cancer patients.
- The results showed that this combined approach significantly outperformed traditional methods, achieving high accuracy in identifying various organs, and suggests it could enhance radiotherapy planning for prostate cancer.
Since the early days of human life on the Earth, our skin has been exposed to different levels of light. Recently, due to inevitable consequences of modern life, humans are not exposed to adequate levels of natural light during the day but they are overexposed to relatively high levels of artificial light at night. Skin is a major target of oxidative stress and the link between aging and oxidative stress is well documented.
View Article and Find Full Text PDFNanopores have recently been developed for the detection and physical characterization of nanoparticles, viruses, proteins, nucleic acids, and other macromolecules in liquids. The method provides the ability to rapidly estimate the size and electrical charge of analytes over a wide range of concentration, potentially with small sample volumes and low cost. Here, we use the technique to measure the mass of nanoparticles and viruses and their sedimentation.
View Article and Find Full Text PDFNanometer-scale pores are capable of detecting the size and concentration of nanometer-sized analytes at low concentrations upon analyzing their translocation through the pore, in small volumes and over a short time without labeling. Here, we present a simple, widely applicable, robust, and precise method to measure the zeta-potential of different nano-objects using nanopores. Zeta-potential i.
View Article and Find Full Text PDFOver the last decade, nanopores have emerged as a new and interesting tool for the study of biological macromolecules like proteins and DNA. While biological pores, especially alpha-haemolysin, have been promising for the detection of DNA, their poor chemical stability limits their use. For this reason, researchers are trying to mimic their behaviour using more stable, solid-state nanopores.
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