AIMC Topic: Image Processing, Computer-Assisted

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Image-based deep learning model using DNA methylation data predicts the origin of cancer of unknown primary.

Neoplasia (New York, N.Y.)
Cancer of unknown primary (CUP) is a rare type of metastatic cancer in which the origin of the tumor is unknown. Since the treatment strategy for patients with metastatic tumors depends on knowing the primary site, accurate identification of the orig...

Non-invasive screening of bladder cancer using digital microfluidics and FLIM technology combined with deep learning.

Journal of biophotonics
Non-invasive screening for bladder cancer is crucial for treatment and postoperative follow-up. This study combines digital microfluidics (DMF) technology with fluorescence lifetime imaging microscopy (FLIM) for urine analysis and introduces a novel ...

Using machine learning to automatically measure kyphotic and lordotic angle measurements on radiographs for children with adolescent idiopathic scoliosis.

Medical engineering & physics
Measuring the kyphotic angle (KA) and lordotic angle (LA) on lateral radiographs is important to truly diagnose children with adolescent idiopathic scoliosis. However, it is a time-consuming process to measure the KA because the endplate of the upper...

Prostate cancer diagnosis based on multi-parametric MRI, clinical and pathological factors using deep learning.

Scientific reports
Prostate cancer is one of the most common and fatal diseases among men, and its early diagnosis can have a significant impact on the treatment process and prevent mortality. Since it does not have apparent clinical symptoms in the early stages, it is...

Explainable AI based automated segmentation and multi-stage classification of gastroesophageal reflux using machine learning techniques.

Biomedical physics & engineering express
Presently, close to two million patients globally succumb to gastrointestinal reflux diseases (GERD). Video endoscopy represents cutting-edge technology in medical imaging, facilitating the diagnosis of various gastrointestinal ailments including sto...

ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging.

Journal of imaging informatics in medicine
As the adoption of artificial intelligence (AI) systems in radiology grows, the increase in demand for greater bandwidth and computational resources can lead to greater infrastructural costs for healthcare providers and AI vendors. To that end, we de...

Reliable object tracking by multimodal hybrid feature extraction and transformer-based fusion.

Neural networks : the official journal of the International Neural Network Society
Visual object tracking, which is primarily based on visible light image sequences, encounters numerous challenges in complicated scenarios, such as low light conditions, high dynamic ranges, and background clutter. To address these challenges, incorp...

Medical image registration via neural fields.

Medical image analysis
Image registration is an essential step in many medical image analysis tasks. Traditional methods for image registration are primarily optimization-driven, finding the optimal deformations that maximize the similarity between two images. Recent learn...

Uncertainty-aware multiple-instance learning for reliable classification: Application to optical coherence tomography.

Medical image analysis
Deep learning classification models for medical image analysis often perform well on data from scanners that were used to acquire the training data. However, when these models are applied to data from different vendors, their performance tends to dro...

Preoperative CT-based radiomics and deep learning model for predicting risk stratification of gastric gastrointestinal stromal tumors.

Medical physics
BACKGROUND: Gastrointestinal stromal tumors (GISTs) are clinically heterogeneous with various malignant potential in different individuals. It is crucial to explore a reliable method for preoperative risk stratification of gastric GISTs noninvasively...