Best AI tools for< Ct Imaging Technician >

InformAI is a technology company dedicated to advancing healthcare through the development of AI-driven solutions. We focus on crafting high-quality, AI-driven enterprise software solutions that address specific clinical needs. We target critical medical fields including radiology, radiation oncology, and high acuity informatics. Our portfolio, featuring our flagship RadOncAI and our development pipeline products of SinusAI and TransplantAI, is designed to deliver impactful solutions that enhance healthcare quality, safety and efficiency.

FPOV is an AI application that helps businesses transform into digital leaders by providing services in leadership, technology operations, people/culture, and artificial intelligence. The application offers workshops, strategies, analysis, support, and advisory services to help organizations succeed in the digital age. FPOV aims to be world-class thought leaders in navigating the constantly changing digital dynamics that impact organizations and people.

BetterMedicine is an AI software designed for cancer diagnostics and detection. It offers AI-powered solutions to enhance patient outcomes and drive efficiency in radiology workflows. The software is expertly designed by medical professionals and AI specialists, providing trusted and clinically validated solutions. BetterMedicine aims to address inefficiencies in radiology by integrating AI-powered software for detecting lesions on CT scans seamlessly into the workflow, thereby improving efficiency and reducing the risk of oversight. The application focuses on improving patient outcomes, reducing errors, and enhancing the wellbeing of radiology professionals.

FuseMedML is a Python framework designed to accelerate machine learning-based discovery in the medical field by promoting code reuse. It provides a flexible design concept where data is stored in a nested dictionary, allowing easy handling of multi-modality information. The framework includes components for creating custom models, loss functions, metrics, and data processing operators. Additionally, FuseMedML offers 'batteries included' key components such as fuse.data for data processing, fuse.eval for model evaluation, and fuse.dl for reusable deep learning components. It supports PyTorch and PyTorch Lightning libraries and encourages the creation of domain extensions for specific medical domains.

Awesome Mamba is a curated collection of groundbreaking research papers and articles on Mamba Architecture, a pioneering framework in deep learning known for its selective state spaces and efficiency in processing complex data structures. The repository offers a comprehensive exploration of Mamba architecture through categorized research papers covering various domains like visual recognition, speech processing, remote sensing, video processing, activity recognition, image enhancement, medical imaging, reinforcement learning, natural language processing, 3D recognition, multi-modal understanding, time series analysis, graph neural networks, point cloud analysis, and tabular data handling.

MOOSE 2.0 is a leaner, meaner, and stronger tool for 3D medical image segmentation. It is built on the principles of data-centric AI and offers a wide range of segmentation models for both clinical and preclinical settings. MOOSE 2.0 is also versatile, allowing users to use it as a command-line tool for batch processing or as a library package for individual processing in Python projects. With its improved speed, accuracy, and flexibility, MOOSE 2.0 is the go-to tool for segmentation tasks.

This repository contains a collection of papers and code for the CVPR 2024 conference. The papers cover a wide range of topics in computer vision, including object detection, image segmentation, image generation, and video analysis. The code provides implementations of the algorithms described in the papers, making it easy for researchers and practitioners to reproduce the results and build upon the work of others. The repository is maintained by a team of researchers at the University of California, Berkeley.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

The repository 'LLM-for-Healthcare' provides a comprehensive survey of large language models (LLMs) for healthcare, covering data, technology, applications, and accountability and ethics. It includes information on various LLM models, training data, evaluation methods, and computation costs. The repository also discusses tasks such as NER, text classification, question answering, dialogue systems, and generation of medical reports from images in the healthcare domain.

TotalSegmentator is a 3D Slicer extension designed for fully automatic whole body CT segmentation using the 'TotalSegmentator' AI model. The computation time is less than one minute, making it efficient for research purposes. Users can set up GPU acceleration for faster segmentation. The tool provides a user-friendly interface for loading CT images, creating segmentations, and displaying results in 3D. Troubleshooting steps are available for common issues such as failed computation, GPU errors, and inaccurate segmentations. Contributions to the extension are welcome, following 3D Slicer contribution guidelines.

Chinese-Tiny-LLM is a repository containing procedures for cleaning Chinese web corpora and pre-training code. It introduces CT-LLM, a 2B parameter language model focused on the Chinese language. The model primarily uses Chinese data from a 1,200 billion token corpus, showing excellent performance in Chinese language tasks. The repository includes tools for filtering, deduplication, and pre-training, aiming to encourage further research and innovation in language model development.

AI-Catalog is a curated list of AI tools, platforms, and resources across various domains. It serves as a comprehensive repository for users to discover and explore a wide range of AI applications. The catalog includes tools for tasks such as text-to-image generation, summarization, prompt generation, writing assistance, code assistance, developer tools, low code/no code tools, audio editing, video generation, 3D modeling, search engines, chatbots, email assistants, fun tools, gaming, music generation, presentation tools, website builders, education assistants, autonomous AI agents, photo editing, AI extensions, deep face/deep fake detection, text-to-speech, startup tools, SQL-related AI tools, education tools, and text-to-video conversion.

LangPort is an open-source platform for serving large language models. It aims to provide a super fast LLM inference service with core features including Huggingface transformers support, distributed serving system, streaming generation, batch inference, and support for various model architectures. It offers compatibility with OpenAI, FauxPilot, HuggingFace, and Tabby APIs. The project supports model architectures like LLaMa, GLM, GPT2, and GPT Neo, and has been tested with models such as NingYu, Vicuna, ChatGLM, and WizardLM. LangPort also provides features like dynamic batch inference, int4 quantization, and generation logprobs parameter.

WebScout is a versatile tool that allows users to search for anything using Google, DuckDuckGo, and phind.com. It contains AI models, can transcribe YouTube videos, generate temporary email and phone numbers, has TTS support, webai (terminal GPT and open interpreter), and offline LLMs. It also supports features like weather forecasting, YT video downloading, temp mail and number generation, text-to-speech, advanced web searches, and more.

Linly-Talker is an innovative digital human conversation system that integrates the latest artificial intelligence technologies, including Large Language Models (LLM) 🤖, Automatic Speech Recognition (ASR) 🎙️, Text-to-Speech (TTS) 🗣️, and voice cloning technology 🎤. This system offers an interactive web interface through the Gradio platform 🌐, allowing users to upload images 📷 and engage in personalized dialogues with AI 💬.

Paper-Reading-ConvAI is a repository that contains a list of papers, datasets, and resources related to Conversational AI, mainly encompassing dialogue systems and natural language generation. This repository is constantly updating.

Vertex AI is a platform for end-to-end model development. It consist of core components that make the processes of MLOps possible for design patterns of all types.

Minic is a chess engine developed for learning about chess programming and modern C++. It is compatible with CECP and UCI protocols, making it usable in various software. Minic has evolved from a one-file code to a more classic C++ style, incorporating features like evaluation tuning, perft, tests, and more. It has integrated NNUE frameworks from Stockfish and Seer implementations to enhance its strength. Minic is currently ranked among the top engines with an Elo rating around 3400 at CCRL scale.

Arno's Iptables Firewall (AIF) is a single- & multi-homed firewall script with DSL/ADSL support. It is a free software distributed under the GNU GPL License. The script provides a comprehensive set of configuration files and plugins for setting up and managing firewall rules, including support for NAT, load balancing, and multirouting. It offers detailed instructions for installation and configuration, emphasizing security best practices and caution when modifying settings. The script is designed to protect against hostile attacks by blocking all incoming traffic by default and allowing users to configure specific rules for open ports and network interfaces.

PromptAgent is a repository for a novel automatic prompt optimization method that crafts expert-level prompts using language models. It provides a principled framework for prompt optimization by unifying prompt sampling and rewarding using MCTS algorithm. The tool supports different models like openai, palm, and huggingface models. Users can run PromptAgent to optimize prompts for specific tasks by strategically sampling model errors, generating error feedbacks, simulating future rewards, and searching for high-reward paths leading to expert prompts.

I am a Radiology assistant specifically programmed to assist with radiology-related questions and differential diagnoses. Type a disease, question, or imaging findings and I will do the rest. You can even upload images (MR, CT, etc) and ask me the diagnosis.

Expert in PET/CT imaging, focusing on oncology, cardiology, neurology

X線CTと画像Viewer開発に特化した技術的アドバイザー

Translates CT cannabis strain names to true names, with detailed descriptions.