Search Results for author: Jussi Tohka

Found 20 papers, 11 papers with code

No-Clean-Reference Image Super-Resolution: Application to Electron Microscopy

no code implementations16 Jan 2024 Mohammad Khateri, Morteza Ghahremani, Alejandra Sierra, Jussi Tohka

The inability to acquire clean high-resolution (HR) electron microscopy (EM) images over a large brain tissue volume hampers many neuroscience studies.

Image Super-Resolution

Convolutional Neural Networks for Automatic Detection of Intact Adenovirus from TEM Imaging with Debris, Broken and Artefacts Particles

no code implementations30 Oct 2023 Olivier Rukundo, Andrea Behanova, Riccardo de Feo, Seppo Ronkko, Joni Oja, Jussi Tohka

To overcome the challenge, due to such a presence, we developed a software tool for semi-automatic annotation and segmentation of adenoviruses and a software tool for automatic segmentation and detection of intact adenoviruses in TEM imaging systems.

Self-Supervised Super-Resolution Approach for Isotropic Reconstruction of 3D Electron Microscopy Images from Anisotropic Acquisition

no code implementations19 Sep 2023 Mohammad Khateri, Morteza Ghahremani, Alejandra Sierra, Jussi Tohka

To overcome this limitation, we propose a novel deep-learning (DL)-based self-supervised super-resolution approach that computationally reconstructs isotropic 3DEM from the anisotropic acquisition.


Multi-Objective Genetic Algorithm for Multi-View Feature Selection

1 code implementation26 May 2023 Vandad Imani, Carlos Sevilla-Salcedo, Elaheh Moradi, Vittorio Fortino, Jussi Tohka

However, the use of multi-view data leads to an increase in high-dimensional data, which poses significant challenges for the prediction models that can lead to poor generalization.

feature selection

Sauron U-Net: Simple automated redundancy elimination in medical image segmentation via filter pruning

1 code implementation27 Sep 2022 Juan Miguel Valverde, Artem Shatillo, Jussi Tohka

We present Sauron, a filter pruning method that eliminates redundant feature maps by discarding the corresponding filters with automatically-adjusted layer-specific thresholds.

Image Segmentation Medical Image Segmentation +1

Multi-task longitudinal forecasting with missing values on Alzheimer's Disease

no code implementations13 Jan 2022 Carlos Sevilla-Salcedo, Vandad Imani, Pablo M. Olmos, Vanessa Gómez-Verdejo, Jussi Tohka

Machine learning techniques typically applied to dementia forecasting lack in their capabilities to jointly learn several tasks, handle time dependent heterogeneous data and missing values.

Imputation Variational Inference

gACSON software for automated segmentation and morphology analyses of myelinated axons in 3D electron microscopy

1 code implementation13 Dec 2021 Andrea Behanova, Ali Abdollahzadeh, Ilya Belevich, Eija Jokitalo, Alejandra Sierra, Jussi Tohka

In this work, we introduce a freely available Matlab-based gACSON software for visualization, segmentation, assessment, and morphology analysis of myelinated axons in 3D-EM volumes of brain tissue samples.


Comparison of single and multitask learning for predicting cognitive decline based on MRI data

1 code implementation21 Sep 2021 Vandad Imani, Mithilesh Prakash, Marzieh Zare, Jussi Tohka

The Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) is a neuropsychological tool that has been designed to assess the severity of cognitive symptoms of dementia.

Domain Adaptation Multi-target regression +2

Automatic cerebral hemisphere segmentation in rat MRI with lesions via attention-based convolutional neural networks

1 code implementation4 Aug 2021 Juan Miguel Valverde, Artem Shatillo, Riccardo de Feo, Jussi Tohka

We present MedicDeepLabv3+, a convolutional neural network that is the first completely automatic method to segment cerebral hemispheres in magnetic resonance (MR) volumes of rats with lesions.

Skull Stripping

Region-wise Loss for Biomedical Image Segmentation

1 code implementation3 Aug 2021 Juan Miguel Valverde, Jussi Tohka

We show that, under the proposed RW loss framework, certain loss functions, such as Active Contour and Boundary loss, can be reformulated similarly with appropriate RW maps, thus revealing their underlying similarities and a new perspective to understand these loss functions.

Image Segmentation Semantic Segmentation

Evaluation of machine learning algorithms for Health and Wellness applications: a tutorial

1 code implementation31 Aug 2020 Jussi Tohka, Mark van Gils

Research on decision support applications in healthcare, such as those related to diagnosis, prediction, treatment planning, etc., have seen enormously increased interest recently.

BIG-bench Machine Learning

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

4 code implementations9 Feb 2020 Razvan V. Marinescu, Neil P. Oxtoby, Alexandra L. Young, Esther E. Bron, Arthur W. Toga, Michael W. Weiner, Frederik Barkhof, Nick C. Fox, Arman Eshaghi, Tina Toni, Marcin Salaterski, Veronika Lunina, Manon Ansart, Stanley Durrleman, Pascal Lu, Samuel Iddi, Dan Li, Wesley K. Thompson, Michael C. Donohue, Aviv Nahon, Yarden Levy, Dan Halbersberg, Mariya Cohen, Huiling Liao, Tengfei Li, Kaixian Yu, Hongtu Zhu, Jose G. Tamez-Pena, Aya Ismail, Timothy Wood, Hector Corrada Bravo, Minh Nguyen, Nanbo Sun, Jiashi Feng, B. T. Thomas Yeo, Gang Chen, Ke Qi, Shiyang Chen, Deqiang Qiu, Ionut Buciuman, Alex Kelner, Raluca Pop, Denisa Rimocea, Mostafa M. Ghazi, Mads Nielsen, Sebastien Ourselin, Lauge Sorensen, Vikram Venkatraghavan, Keli Liu, Christina Rabe, Paul Manser, Steven M. Hill, James Howlett, Zhiyue Huang, Steven Kiddle, Sach Mukherjee, Anais Rouanet, Bernd Taschler, Brian D. M. Tom, Simon R. White, Noel Faux, Suman Sedai, Javier de Velasco Oriol, Edgar E. V. Clemente, Karol Estrada, Leon Aksman, Andre Altmann, Cynthia M. Stonnington, Yalin Wang, Jianfeng Wu, Vivek Devadas, Clementine Fourrier, Lars Lau Raket, Aristeidis Sotiras, Guray Erus, Jimit Doshi, Christos Davatzikos, Jacob Vogel, Andrew Doyle, Angela Tam, Alex Diaz-Papkovich, Emmanuel Jammeh, Igor Koval, Paul Moore, Terry J. Lyons, John Gallacher, Jussi Tohka, Robert Ciszek, Bruno Jedynak, Kruti Pandya, Murat Bilgel, William Engels, Joseph Cole, Polina Golland, Stefan Klein, Daniel C. Alexander

TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease.

Alzheimer's Disease Detection Disease Prediction

RatLesNetv2: A Fully Convolutional Network for Rodent Brain Lesion Segmentation

1 code implementation24 Jan 2020 Juan Miguel Valverde, Artem Shatillo, Riccardo de Feo, Olli Gröhn, Alejandra Sierra, Jussi Tohka

RatLesNetv2 obtained similar to higher Dice coefficient values than the other ConvNets and it produced much more realistic and compact segmentations with notably fewer holes and lower Hausdorff distance.

Image Segmentation Lesion Segmentation +1

Cylindrical Shape Decomposition for 3D Segmentation of Tubular Objects

3 code implementations1 Nov 2019 Ali Abdollahzadeh, Alejandra Sierra, Jussi Tohka

We develop a cylindrical shape decomposition (CSD) algorithm to decompose an object, a union of several tubular structures, into its semantic components.

Object Semantic Segmentation

Predicting intelligence based on cortical WM/GM contrast, cortical thickness and volumetry

no code implementations9 Sep 2019 Juan Miguel Valverde, Vandad Imani, John D. Lewis, Jussi Tohka

These last two measurements were derived from the T1-weighted MR images using cortical surfaces produced by the CIVET pipeline.

Bayesian Receiver Operating Characteristic Metric for Linear Classifiers

no code implementations23 Aug 2019 Syeda Sakira Hassan, Heikki Huttunen, Jari Niemi, Jussi Tohka

We derive a closed-form solution of the proposed accuracy metric for any linear binary classifier under the Gaussianity assumption, and study the accuracy of the proposed estimator using simulated and real-world data.

Automatic Rodent Brain MRI Lesion Segmentation with Fully Convolutional Networks

no code implementations23 Aug 2019 Juan Miguel Valverde, Artem Shatillo, Riccardo de Feo, Olli Gröhn, Alejandra Sierra, Jussi Tohka

Several automatic methods have been developed for different human brain MRI segmentation, but little research has targeted automatic rodent lesion segmentation.

Image Segmentation Lesion Segmentation +3

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