Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment
This review delves into the most recent advancements in applying artificial intelligence (AI)
within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors …
within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors …
Vision transformer promotes cancer diagnosis: A comprehensive review
X Jiang, S Wang, Y Zhang - Expert Systems with Applications, 2024 - Elsevier
Background The approaches based on vision transformers (ViTs) are advancing the field of
medical artificial intelligence (AI) and cancer diagnosis. Recently, many researchers have …
medical artificial intelligence (AI) and cancer diagnosis. Recently, many researchers have …
Advancing Brain Tumor Classification through Fine-Tuned Vision Transformers: A Comparative Study of Pre-Trained Models
This paper presents a comprehensive study on the classification of brain tumor images
using five pre-trained vision transformer (ViT) models, namely R50-ViT-l16, ViT-l16, ViT-l32 …
using five pre-trained vision transformer (ViT) models, namely R50-ViT-l16, ViT-l16, ViT-l32 …
VITALT: a robust and efficient brain tumor detection system using vision transformer with attention and linear transformation
S Poornam, JJR Angelina - Neural Computing and Applications, 2024 - Springer
Brain tumor detection and classification are crucial steps in evaluating life-threatening
abnormal tissues to provide appropriate treatment plans. For clinical assessment, Magnetic …
abnormal tissues to provide appropriate treatment plans. For clinical assessment, Magnetic …
A fine-tuned transformer model for brain tumor detection and classification
The identification and classification of brain tumors from medical images is a challenging
task, which plays a crucial role in treatment planning. In recent times, the transformer models …
task, which plays a crucial role in treatment planning. In recent times, the transformer models …
Realism in Action: Anomaly-Aware Diagnosis of Brain Tumors from Medical Images Using YOLOv8 and DeiT
SMH Hashemi, L Safari, AD Taromi - arXiv preprint arXiv:2401.03302, 2024 - arxiv.org
In the field of medical sciences, reliable detection and classification of brain tumors from
images remains a formidable challenge due to the rarity of tumors within the population of …
images remains a formidable challenge due to the rarity of tumors within the population of …
A Performance Analysis of Brain Tumor Classification from MRI Images using Vision Transformers and CNN-based Classifiers
R Jahangir, T Sakib, R Haque… - 2023 26th International …, 2023 - ieeexplore.ieee.org
Abnormal growth of cells inside the brain or skull may result in brain tumors, a deadly
neurological condition. Every year, the number of people dying of this condition is …
neurological condition. Every year, the number of people dying of this condition is …
A Deep Learning‑Based Approach for Cervical Cancer Classification Using 3D CNN and Vision Transformer
K Abinaya, B Sivakumar - Journal of imaging informatics in medicine, 2024 - Springer
Cervical cancer is a significant health problem worldwide, and early detection and treatment
are critical to improving patient outcomes. To address this challenge, a deep learning (DL) …
are critical to improving patient outcomes. To address this challenge, a deep learning (DL) …
Traumatic meningeal enhancement detection by deep learning-based biomedical image analysis and handcrafted features extraction
MS Uddin, NJ Nidhi, S Yesmin, PK Roy - 2024 - dspace.bracu.ac.bd
Traumatic Meningeal Enhancement (TME) is a critical medical condition characterized by
abnormal enhancement of the meninges following trauma, often observed in medical …
abnormal enhancement of the meninges following trauma, often observed in medical …
[引用][C] ENHANCING QUALITY AND REDUCING COSTS IN THE PRINTING INDUSTRY
MA Arunkumar - International Development Planning Review, 2023