Medical Device and Diagnostic Industry (MD+DI)

The AI Era: How Deep Learning is Overcoming Data Scarcity in Medical Imaging

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...
Medscape

New Deep Learning Model Parcellates Brain Using Only dMRI

A novel hierarchical deep learning framework enables direct Desikan-Killiany brain parcellation using only diffusion ...
IEEE

Interpretable Semantic Medical Image Segmentation with Style and Confidence

Abstract: The scarcity of semantically labelled data presents major challenges for medical image segmentation using deep learning models, and the ”black-box” nature of these models inherently limits ...
IEEE

EICSeg: Universal Medical Image Segmentation via Explicit In-Context Learning

Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...
GitHub

What is Deep Learning?

Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...
GitHub

4D- LATTE : 4D Radar Drivable Area Automatic Labelling Tools using Deep Learning

First 4D Radar Automatic Labelling tools using Segment Anything (SA) drivable area segmentation on camera using Deep Learning for Autonomous Vehicle. KAIST-Radar (K-Radar) (provided by 'AVELab') is a ...
Frontiers

Traditional machine learning in biomedical image analysis: before you go too deep

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...
Scientific Research Publishing

From U-Net to Swin-Unet Transformers: The Next-Generation Advances in Brain Tumor Segmentation with Deep Learning ()

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...
Scientific Research Publishing

Minaee, S., Boykov, Y.Y., Porikli, F., Plaza, A.J., Kehtarnavaz, N. and Terzopoulos, D. (2021) Image Segmentation Using Deep Learning: A Survey. IEEE Transactions on Pattern ...

ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...