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Machine Heart
Machine Heart
May 21, 2026 · Artificial Intelligence

How GaussianPile Enables 3DGS to Reconstruct Internal Structures from Slice‑Based Volumetric Images

GaussianPile extends 3D Gaussian Splatting to slice‑based volumetric data by embedding finite slice thickness and focus depth into the rendering pipeline, achieving up to 20‑26× compression, 8‑minute training, and superior 2D/3D PSNR/SSIM compared with HEVC, INR/NeRF and standard 3DGS on medical imaging datasets.

3DGSGaussianPilecompression
0 likes · 11 min read
How GaussianPile Enables 3DGS to Reconstruct Internal Structures from Slice‑Based Volumetric Images
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
May 14, 2026 · Artificial Intelligence

Turning Multi‑Teacher Conflict into Dynamic Constraints: Robust Reasoning Alignment for Multimodal LLMs (ICML 2026)

APO (Autonomous Preference Optimization) converts the drift and conflict among multiple teacher multimodal LLMs into dynamic negative constraints while treating consensus as a positive preference, enabling robust concept alignment and superior diagnostic accuracy on the CXR‑MAX benchmark, as demonstrated by extensive ICML‑2026 experiments.

APOICML 2026Multimodal LLM
0 likes · 11 min read
Turning Multi‑Teacher Conflict into Dynamic Constraints: Robust Reasoning Alignment for Multimodal LLMs (ICML 2026)
AI Explorer
AI Explorer
Apr 1, 2026 · Industry Insights

AI Technology Daily: Key Developments on April 1, 2026

The roundup highlights OpenAI's AI banking assistant, Apple's AI‑enhanced iOS 27 keyboard, UBTech's robot revenue surge, the HorusEye self‑supervised X‑ray model, record OpenAI financing, Microsoft's massive AI investment, Anthropic's product challenges, NVIDIA's AI‑Agent blueprint, deterministic agent production, and a new parallel decoding breakthrough from Stanford and Princeton.

AIAppleFunding
0 likes · 5 min read
AI Technology Daily: Key Developments on April 1, 2026
HyperAI Super Neural
HyperAI Super Neural
Feb 13, 2026 · Artificial Intelligence

UCL Team Uses Federated Learning to Train Blood Morphology Models Without Sharing Data

A UCL computer‑science team presents a federated learning framework for white‑blood‑cell morphology analysis that preserves patient privacy, leverages heterogeneous clinical slide data from multiple sites, and achieves superior cross‑site performance and generalisation to unseen institutions compared with centralized training.

Blood MorphologyDINOv2Federated Learning
0 likes · 14 min read
UCL Team Uses Federated Learning to Train Blood Morphology Models Without Sharing Data
AI Programming Lab
AI Programming Lab
Jan 13, 2026 · Artificial Intelligence

How I Produced a 45‑Page, SCI‑Ready Literature Review Using Claude Code

The article demonstrates a step‑by‑step workflow that treats Claude Code as a high‑quality information processor, feeding it curated open‑source and closed‑access papers via Zotero, using plan mode to learn journal style, generating Markdown guides, and finally producing a 45‑page, Nature‑style review ready for top‑tier journal submission.

AIClaude CodeLiterature Review
0 likes · 8 min read
How I Produced a 45‑Page, SCI‑Ready Literature Review Using Claude Code
AI Frontier Lectures
AI Frontier Lectures
Sep 7, 2025 · Artificial Intelligence

How Dynamic Snake and Pinwheel Convolutions Boost Small‑Target Segmentation Accuracy

This article reviews two recent AI papers—Dynamic Snake Convolution with topological constraints for tubular structure segmentation and Pinwheel‑shaped Convolution with scale‑based dynamic loss for infrared small‑target detection—detailing their methods, innovations, experimental gains, and future research directions.

Deep Learningdynamic convolutionmedical imaging
0 likes · 7 min read
How Dynamic Snake and Pinwheel Convolutions Boost Small‑Target Segmentation Accuracy
AI Frontier Lectures
AI Frontier Lectures
Apr 18, 2025 · Artificial Intelligence

DiffDenoise: Conditional Diffusion Transforms Medical Image Denoising

DiffDenoise introduces a three‑stage self‑supervised pipeline that combines a blind‑spot network, conditional diffusion modeling, and stabilized reverse diffusion sampling to dramatically improve medical image denoising performance on both synthetic and real datasets, while also offering a fast distilled version for practical deployment.

Diffusion ModelsImage Processingmedical imaging
0 likes · 10 min read
DiffDenoise: Conditional Diffusion Transforms Medical Image Denoising
iKang Technology Team
iKang Technology Team
Nov 12, 2024 · Artificial Intelligence

AI Applications in Medical Imaging for Enhanced Disease Detection

AI-driven medical imaging leverages deep learning and massive datasets to detect lesions—often earlier than human eyes— with high accuracy and speed, reducing fatigue‑related errors and workload, while challenges such as data quality, interpretability, privacy, and regulatory compliance must be addressed for widespread clinical adoption.

AIAI applicationsAI in healthcare
0 likes · 5 min read
AI Applications in Medical Imaging for Enhanced Disease Detection
Baidu Geek Talk
Baidu Geek Talk
Sep 23, 2024 · Artificial Intelligence

Intelligent Early Screening System for Malignant Skin Tumors Based on PaddleX Low‑Code AI

The Meikel Studio team created an intelligent early‑screening system for malignant skin tumors on the PaddleX low‑code AI platform, which automatically captures dermatoscopic images, segments lesions with the PP‑LiteSeg model, achieves high accuracy (mIoU 0.868) and rapid inference, and offers one‑click deployment via RESTful API to improve diagnosis efficiency and support future medical‑imaging applications.

AI segmentationModel DeploymentPaddleX
0 likes · 9 min read
Intelligent Early Screening System for Malignant Skin Tumors Based on PaddleX Low‑Code AI
Baidu Tech Salon
Baidu Tech Salon
Aug 27, 2024 · Artificial Intelligence

How PaddleX Enables Early Detection of Malignant Skin Tumors with AI Segmentation

This article examines the urgent need for early skin cancer detection in China, outlines the challenges of dermatological imaging, and details a low‑code PaddleX solution that leverages PP‑LiteSeg‑T for data preparation, model training, optimization, and deployment to improve diagnostic accuracy and efficiency.

AIDeep LearningPaddleX
0 likes · 10 min read
How PaddleX Enables Early Detection of Malignant Skin Tumors with AI Segmentation
160 Technical Team
160 Technical Team
Jul 29, 2024 · Artificial Intelligence

How YOLO Transforms Medical Report Screening and Occlusion Detection

Leveraging the YOLO family of deep‑learning models, this study demonstrates efficient filtering of irrelevant medical images, accurate classification of textual reports, and robust detection of occluding objects, achieving high precision and speed on both CPU and GPU, while outlining training details, performance metrics, and future improvements.

Deep LearningYOLOmedical imaging
0 likes · 17 min read
How YOLO Transforms Medical Report Screening and Occlusion Detection
Baidu Geek Talk
Baidu Geek Talk
Jun 3, 2024 · Artificial Intelligence

How an AI Code Assistant Cut Medical Imaging Data Processing Time by 9×

A graduate student and his lab used Baidu Comate, an AI‑powered coding assistant, to automate repetitive Python scripts for converting 150 GB of DICOM images to PNG, reducing a week‑long, three‑person effort to two days for a single developer and boosting overall team efficiency.

AIAI code assistantBaidu Comate
0 likes · 8 min read
How an AI Code Assistant Cut Medical Imaging Data Processing Time by 9×
Baidu Tech Salon
Baidu Tech Salon
May 30, 2024 · Artificial Intelligence

How AI Code Assistant Baidu Comate Boosted Medical Imaging Processing by 9×

A graduate student’s lab cut the time to process 150 GB of medical imaging data from one week for three people to two days for one person by using Baidu Comate’s AI‑driven code generation, annotation, and private‑knowledge enhancement features, achieving over nine‑fold productivity gains.

AI code assistantBaidu Comatecode-generation
0 likes · 8 min read
How AI Code Assistant Baidu Comate Boosted Medical Imaging Processing by 9×
Python Crawling & Data Mining
Python Crawling & Data Mining
Sep 24, 2021 · Artificial Intelligence

How to Build a 3D CNN for CT Scan Classification with TensorFlow

This tutorial walks through constructing, training, and evaluating a 3D convolutional neural network in TensorFlow to classify CT scans for viral pneumonia, covering data preprocessing, dynamic learning rates, early stopping, and single‑scan prediction with full code examples.

3D CNNCT scan classificationDeep Learning
0 likes · 15 min read
How to Build a 3D CNN for CT Scan Classification with TensorFlow
HaoDF Tech Team
HaoDF Tech Team
Feb 2, 2021 · Artificial Intelligence

AI‑Based Structuring of Medical Examination Reports: OCR, Text Detection, Classification, and NER

This article describes how a Chinese online medical platform tackled the large‑scale extraction and structuring of hospital report images by combining OCR, deep‑learning text‑region detection, fast text classification, and advanced NER techniques, detailing challenges, algorithm choices, performance results, and remaining issues.

AINERNLP
0 likes · 19 min read
AI‑Based Structuring of Medical Examination Reports: OCR, Text Detection, Classification, and NER
Tencent Tech
Tencent Tech
Jan 29, 2021 · Artificial Intelligence

Can AI Revolutionize Blood Cell Analysis? Tencent and Mindray’s New Partnership

Tencent AI Lab and Shenzhen Mindray have signed an AI cooperation framework to develop an automated blood cell analysis system that leverages machine learning, computer vision, and cloud solutions, aiming to improve early disease screening, reduce costs, and address the shortage of skilled microscopy personnel.

AIBlood AnalysisHealthcare
0 likes · 6 min read
Can AI Revolutionize Blood Cell Analysis? Tencent and Mindray’s New Partnership
Tencent Cloud Developer
Tencent Cloud Developer
May 11, 2018 · Artificial Intelligence

Imaging Methods and Image Analysis Overview

The talk by Tencent Cloud senior researcher Ji Yongnan reviews imaging modalities, low‑ to high‑level processing, the rise of deep‑learning CNNs over traditional handcrafted methods, and their deployment in classification, detection, segmentation, moderation, medical analysis, OCR, and other real‑world applications.

AIImage Analysisimaging
0 likes · 9 min read
Imaging Methods and Image Analysis Overview
Alibaba Cloud Developer
Alibaba Cloud Developer
May 22, 2017 · Artificial Intelligence

AI, Big Data, and Graph Computing Take Center Stage at ACM TURC 2017

The ACM TURC 2017 conference in Shanghai gathered Turing Award laureates, leading Chinese scholars, and Alibaba executives, highlighting breakthroughs in artificial intelligence, big data, streaming and graph computing, and showcasing AI-driven medical imaging diagnostics and collaborative research initiatives between industry and academia.

Artificial Intelligencegraph computingmedical imaging
0 likes · 4 min read
AI, Big Data, and Graph Computing Take Center Stage at ACM TURC 2017