CHAOS-evaluation

Segmentation evaluator

Evaluates segmentation performance in medical imaging using multiple metrics

Evaluation code of CHAOS challenge in MATLAB, Python and Julia languages.

GitHub

57 stars
1 watching
7 forks
Language: MATLAB
last commit: about 5 years ago
Linked from 1 awesome list


Backlinks from these awesome lists:

Related projects:

Repository Description Stars
martinkersner/py-img-seg-eval A Python package providing metrics and tools for evaluating image segmentation models 282
zhourax/vega Develops a multimodal task and dataset to assess vision-language models' ability to handle interleaved image-text inputs. 33
ruixiangcui/agieval Evaluates foundation models on human-centric tasks with diverse exams and question types 712
mfaruqui/eval-word-vectors Tools for evaluating word vectors in various natural language processing tasks 120
mshukor/evalign-icl Evaluating and improving large multimodal models through in-context learning 20
krrishdholakia/betterprompt An API for evaluating the quality of text prompts used in Large Language Models (LLMs) based on perplexity estimation 40
aka-discover/ccmba_cvpr23 Improving semantic segmentation robustness to motion blur using custom data augmentation techniques 5
chenllliang/mmevalpro A benchmarking framework for evaluating Large Multimodal Models by providing rigorous metrics and an efficient evaluation pipeline. 22
benhamner/metrics Provides implementations of various supervised machine learning evaluation metrics in multiple programming languages. 1,630
maluuba/nlg-eval A toolset for evaluating and comparing natural language generation models 1,350
princeton-nlp/charxiv An evaluation suite for assessing chart understanding in multimodal large language models. 77
uzh-rpg/rpg_trajectory_evaluation A toolbox for evaluating trajectory estimates in visual-inertial odometry, providing common methods and error metrics. 1,069
freedomintelligence/mllm-bench Evaluates and compares the performance of multimodal large language models on various tasks 55
sony/pyieoe Develops an interpretable evaluation procedure for off-policy evaluation (OPE) methods to quantify their sensitivity to hyper-parameter choices and/or evaluation policy choices. 31
pkinney/segseg_ex An Elixir module that calculates intersection and classification of two line segments 6