AIMC Topic: Image Processing, Computer-Assisted

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Guided image generation for improved surgical image segmentation.

Medical image analysis
The lack of large datasets and high-quality annotated data often limits the development of accurate and robust machine-learning models within the medical and surgical domains. In the machine learning community, generative models have recently demonst...

DSnet: a new dual-branch network for hippocampus subfield segmentation.

Scientific reports
The hippocampus is a critical component of the brain and is associated with many neurological disorders. It can be further subdivided into several subfields, and accurate segmentation of these subfields is of great significance for diagnosis and rese...

Structure focused neurodegeneration convolutional neural network for modelling and classification of Alzheimer's disease.

Scientific reports
Alzheimer's disease (AD), the predominant form of dementia, is a growing global challenge, emphasizing the urgent need for accurate and early diagnosis. Current clinical diagnoses rely on radiologist expert interpretation, which is prone to human err...

Deep Learning-based Hierarchical Brain Segmentation with Preliminary Analysis of the Repeatability and Reproducibility.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: We developed new deep learning-based hierarchical brain segmentation (DLHBS) method that can segment T1-weighted MR images (T1WI) into 107 brain subregions and calculate the volume of each subregion. This study aimed to evaluate the repeatab...

Adrenal Volume Quantitative Visualization Tool by Multiple Parameters and an nnU-Net Deep Learning Automatic Segmentation Model.

Journal of imaging informatics in medicine
Abnormalities in adrenal gland size may be associated with various diseases. Monitoring the volume of adrenal gland can provide a quantitative imaging indicator for such conditions as adrenal hyperplasia, adrenal adenoma, and adrenal cortical adenoca...

Optimized Wasserstein Deep Convolutional Generative Adversarial Network fostered Groundnut Leaf Disease Identification System.

Network (Bristol, England)
Groundnut is a noteworthy oilseed crop. Attacks by leaf diseases are one of the most important reasons causing low yield and loss of groundnut plant growth, which will directly diminish the yield and quality. Therefore, an Optimized Wasserstein Deep ...

Deep learning classification of ex vivo human colon tissues using spectroscopic optical coherence tomography.

Journal of biophotonics
Screening for colorectal cancer (CRC) with colonoscopy has improved patient outcomes; however, it remains the third leading cause of cancer-related mortality, novel strategies to improve screening are needed. Here, we propose an optical biopsy techni...

Ovarian cancer identification technology based on deep learning and second harmonic generation imaging.

Journal of biophotonics
Ovarian cancer is among the most common gynecological cancers and the eighth leading cause of cancer-related deaths among women worldwide. Surgery is among the most important options for cancer treatment. During surgery, a biopsy is generally require...

An artificial intelligence system for comprehensive pathologic outcome prediction in early gastric cancer through endoscopic image analysis (with video).

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Accurate prediction of pathologic results for early gastric cancer (EGC) based on endoscopic findings is essential in deciding between endoscopic and surgical resection. This study aimed to develop an artificial intelligence (AI) model to...

ELA-Net: An Efficient Lightweight Attention Network for Skin Lesion Segmentation.

Sensors (Basel, Switzerland)
In clinical conditions limited by equipment, attaining lightweight skin lesion segmentation is pivotal as it facilitates the integration of the model into diverse medical devices, thereby enhancing operational efficiency. However, the lightweight des...