AIMC Topic: Image Processing, Computer-Assisted

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Digital pathology systems enabling quality patient care.

Genes, chromosomes & cancer
Pathology laboratories are undergoing digital transformations, adopting innovative technologies to enhance patient care. Digital pathology systems impact clinical, education, and research use cases where pathologists use digital technologies to perfo...

Auto-Segmentation and Classification of Glioma Tumors with the Goals of Treatment Response Assessment Using Deep Learning Based on Magnetic Resonance Imaging.

Neuroinformatics
Glioma is the most common primary intracranial neoplasm in adults. Radiotherapy is a treatment approach in glioma patients, and Magnetic Resonance Imaging (MRI) is a beneficial diagnostic tool in treatment planning. Treatment response assessment in g...

Deep learning for histopathological segmentation of smooth muscle in the urinary bladder.

BMC medical informatics and decision making
BACKGROUND: Histological assessment of smooth muscle is a critical step particularly in staging malignant tumors in various internal organs including  the urinary bladder. Nonetheless, manual segmentation and classification of muscular tissues by pat...

An unsupervised two-step training framework for low-dose computed tomography denoising.

Medical physics
BACKGROUND: Although low-dose computed tomography (CT) imaging has been more widely adopted in clinical practice to reduce radiation exposure to patients, the reconstructed CT images tend to have more noise, which impedes accurate diagnosis. Recently...

Deep-learning based segmentation of ultrasound adipose image for liposuction.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: To develop an automatic and reliable ultrasonic visual system for robot- or computer-assisted liposuction, we examined the use of deep learning for the segmentation of adipose ultrasound images in clinical and educational settings.

Lightweight image super-resolution based multi-order gated aggregation network.

Neural networks : the official journal of the International Neural Network Society
Recently, Transformer-based models are taken much focus on solving the task of image super-resolution (SR) due to their ability to achieve better performance. However, these models combined huge computational cost during the computing self-attention ...

Automated Segmentation of Sacral Chordoma and Surrounding Muscles Using Deep Learning Ensemble.

International journal of radiation oncology, biology, physics
PURPOSE: The manual segmentation of organ structures in radiation oncology treatment planning is a time-consuming and highly skilled task, particularly when treating rare tumors like sacral chordomas. This study evaluates the performance of automated...

Whole Slide Imaging Technology and Its Applications: Current and Emerging Perspectives.

International journal of surgical pathology
. Whole slide imaging (WSI) represents a paradigm shift in pathology, serving as a necessary first step for a wide array of digital tools to enter the field. It utilizes virtual microscopy wherein glass slides are converted into digital slides and ar...

Multi-institutional PET/CT image segmentation using federated deep transformer learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Generalizable and trustworthy deep learning models for PET/CT image segmentation necessitates large diverse multi-institutional datasets. However, legal, ethical, and patient privacy issues challenge sharing of datasets betw...