AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 9581 to 9590 of 10288 articles

Attention-guided multi-scale deep object detection framework for lymphocyte analysis in IHC histological images.

Microscopy (Oxford, England)
Tumor-infiltrating lymphocytes are specialized lymphocytes that can detect and kill cancerous cells. Their detection poses many challenges due to significant morphological variations, overlapping occurrence, artifact regions and high-class resemblanc...

Image Quality Assessment of Deep Learning Image Reconstruction in Torso Computed Tomography Using Tube Current Modulation.

Acta medica Okayama
Novel deep learning image reconstruction (DLIR) reportedly changes the image quality characteristics based on object contrast and image noise. In clinical practice, computed tomography image noise is usually controlled by tube current modulation (TCM...

Clarifications regarding convolutional neural networks-based automatic segmentation of pharyngeal airway sections.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics

Analysing cerebrospinal fluid with explainable deep learning: From diagnostics to insights.

Neuropathology and applied neurobiology
AIM: Analysis of cerebrospinal fluid (CSF) is essential for diagnostic workup of patients with neurological diseases and includes differential cell typing. The current gold standard is based on microscopic examination by specialised technicians and n...

IDEFE algorithm: IDE algorithm optimizes the fuzzy entropy for the gland segmentation.

Mathematical biosciences and engineering : MBE
Breast cancer occurs in the epithelial tissue of the gland, so the accuracy of gland segmentation is crucial to the physician's diagnosis. An innovative technique for breast mammography image gland segmentation is put forth in this paper. In the firs...

COMBINING HI-RESOLUTION SCAN MODE WITH DEEP LEARNING RECONSTRUCTION ALGORITHMS IN CARDIAC CT.

Radiation protection dosimetry
To investigate the impact of combining the high-resolution (Hi-res) scan mode with deep learning image reconstruction (DLIR) algorithm in CT. Two phantoms (Catphan600® and Lungman, small, medium, large size) were CT scanned using combinations of Hi-r...

Image Reconstruction Using Deep Learning for Near-Infrared Optical Tomography: Generalization Assessment.

Advances in experimental medicine and biology
Time is one of the most critical factors in preventing brain lesions due to hypoxic ischemia in preterm infants. Since early detection of low oxygenation is vital and the time window for therapy is narrow, near-infrared optical tomography (NIROT) mus...

Performance of a deep learning enhancement method applied to PET images acquired with a reduced acquisition time.

Nuclear medicine review. Central & Eastern Europe
BACKGROUND: This study aims to evaluate the performance of a deep learning enhancement method in PET images reconstructed with a shorter acquisition time, and different reconstruction algorithms. The impact of the enhancement on clinical decisions wa...

Traditional and deep learning-oriented medical and biological image analysis.

Bratislavske lekarske listy
We investigated various methods for image segmentation and image processing for the segmentation of MRI of human medical data, as well as bioinformatics for the segmentation of brain cell details, in this work. The goal is to demonstrate and bring va...