M. F. Rachmadi

发表

Fuzzy learning vector quantization particle swarm optimization (FLVQ-PSO) and fuzzy neuro generalized learning vector quantization (FN-GLVQ) for automatic early detection system of heart diseases based on real-time electrocardiogram

W. Jatmiko, M. A. Ma'sum, I. M. A. Setiawan, 2012, 2012 Proceedings of SICE Annual Conference (SICE).

Mobile phones as traffic sensors with map matching and privacy considerations

Wisnu Jatmiko, Adi Wibowo, Benny Hardjono, 2012, 2012 International Symposium on Micro-NanoMechatronics and Human Science (MHS).

Modified MultiResUNet for Left Ventricle Segmentation from Echocardiographic Images

Wisma Chaerul Karunianto, W. Jatmiko, M. F. Rachmadi, 2022, 2022 7th International Workshop on Big Data and Information Security (IWBIS).

Hierarchical Vision Transformers for Cardiac Ejection Fraction Estimation

W. Jatmiko, M. F. Rachmadi, Lhuqita Fazry, 2022, 2022 7th International Workshop on Big Data and Information Security (IWBIS).

Limited One-time Sampling Irregularity Map (LOTS-IM) for Automatic Unsupervised Assessment of White Matter Hyperintensities and Multiple Sclerosis Lesions in Structural Brain Magnetic Resonance Images

Daniel Rueckert, Joanna M. Wardlaw, Maria del C. Valdés Hernández, 2019, Comput. Medical Imaging Graph..

Automatic Irregular Texture Detection in Brain MRI Without Human Supervision

Taku Komura, Muhammad Febrian Rachmadi, Maria del C. Valdés Hernández, 2018, MICCAI.

Transfer Learning for Task Adaptation of Brain Lesion Assessment and Prediction of Brain Abnormalities Progression/Regression using Irregularity Age Map in Brain MRI

Taku Komura, Muhammad Febrian Rachmadi, Maria del C. Valdés Hernández, 2018, bioRxiv.

Limited One-time Sampling Irregularity Age Map (LOTS-IAM): Automatic Unsupervised Detection of Brain White Matter Abnormalities in Structural Magnetic Resonance Images

Daniel Rueckert, Hongwei Li, Muhammad Febrian Rachmadi, 2018, bioRxiv.

Segmentation of white matter hyperintensities using convolutional neural networks with global spatial information in routine clinical brain MRI with none or mild vascular pathology

Taku Komura, Muhammad Febrian Rachmadi, Maria del C. Valdés Hernández, 2018, Comput. Medical Imaging Graph..

Deep Learning vs. Conventional Machine Learning: Pilot Study of WMH Segmentation in Brain MRI with Absence or Mild Vascular Pathology

Taku Komura, Muhammad Febrian Rachmadi, Maria del C. Valdés Hernández, 2017, Journal of Imaging.

The Brain/MINDS Marmoset Connectivity Atlas: exploring bidirectional tracing and tractography in the same stereotaxic space

K. Doya, Shin Ishii, Ken Nakae, 2022, bioRxiv.

A dataset of rodent cerebrovasculature from in vivo multiphoton fluorescence microscopy imaging

K. Hynynen, Henrik Skibbe, M. F. Rachmadi, 2022, bioRxiv.

Local and long-distance organization of prefrontal cortex circuits in the marmoset brain

Shin Ishii, Ken Nakae, T. Yamamori, 2022, Neuron.

Automatic Arrhythmia Beat Detection: Algorithm, System, and Implementation

Muhammad Febrian Rachmadi, Wisnu Jatmiko, I Md. Agus Setiawan, 2016 .

Automatic spatial estimation of white matter hyperintensities evolution in brain MRI using disease evolution predictor deep neural networks

Taku Komura, Muhammad Febrian Rachmadi, Joanna Wardlaw, 2019, bioRxiv.

PARTICLE SWARM OPTIMIZATION (PSO) FOR TRAINING OPTIMIZATION ON CONVOLUTIONAL NEURAL NETWORK (CNN)

Adi Wibowo, Dwi Marhaendro Jati Purnomo, Muhammad Febrian Rachmadi, 2016 .

Adaptive traffic signal control system using camera sensor and embedded system

Wisnu Jatmiko, Adi Wibowo, Petrus Mursanto, 2011, TENCON 2011 - 2011 IEEE Region 10 Conference.

Evaluation of Enhanced Learning Techniques for Segmenting Ischaemic Stroke Lesions in Brain Magnetic Resonance Perfusion Images Using a Convolutional Neural Network Scheme

Taku Komura, Muhammad Febrian Rachmadi, Carlos Uziel Perez Malla, 2019, bioRxiv.

Voxel-based irregularity age map (IAM) for brain's white matter hyperintensities in MRI

Muhammad Febrian Rachmadi, Maria del C. Valdés-Hernández, Taku Komura, 2017, 2017 International Conference on Advanced Computer Science and Information Systems (ICACSIS).

Evaluation of Four Supervised Learning Schemes in White Matter Hyperintensities Segmentation in Absence or Mild Presence of Vascular Pathology

Taku Komura, Muhammad Febrian Rachmadi, Maria del C. Valdés Hernández, 2017, MIUA.

COMPARISON OF IMAGE ENHANCEMENT METHODS FOR CHROMOSOME KARYOTYPE IMAGE ENHANCEMENT

Dewa Made Sri Arsa, Muhammad Febrian Rachmadi, Grafika Jati, 2017 .

Classification of Stroke and Non-Stroke Patients from Human Body Movements using Smartphone Videos and Deep Neural Networks

D. Chahyati, M. F. Rachmadi, Zafira Binta Feliandra, 2022, 2022 International Conference on Advanced Computer Science and Information Systems (ICACSIS).

Generalized learning vector quantization particle swarm optimization (GLVQ-PSO) FPGA implementation for real-time electrocardiogram

Wisnu Jatmiko, Yulistiyan Wardhana, M. Febrian Rachmadi, 2016, 2016 International Workshop on Big Data and Information Security (IWBIS).

An automated pipeline to create an atlas of in situ hybridization gene expression data in the adult marmoset brain

T. Shimogori, Henrik Skibbe, Michal Byra, 2023, ArXiv.

Improving Segmentation of Objects with Varying Sizes in Biomedical Images using Instance-wise and Center-of-Instance Segmentation Loss Function

Henrik Skibbe, M. F. Rachmadi, Charissa Poon, 2023, ArXiv.

Improving the prediction of white matter hyperintensities evolution in brain MRI of patients with small vessel disease using stroke lesions information

J. Wardlaw, Henrik Skibbe, S. Makin, 2022, bioRxiv.

Predicting the Evolution of White Matter Hyperintensities in Brain MRI using Generative Adversarial Networks and Irregularity Map

Taku Komura, Muhammad Febrian Rachmadi, Joanna M. Wardlaw, 2019, bioRxiv.

Dilated Saliency U-Net for White Matter Hyperintensities Segmentation Using Irregularity Age Map

Taku Komura, Muhammad Febrian Rachmadi, Yunhee Jeong, 2019, bioRxiv.