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Publications

50 latest publications

[1]
G. D. Mawla et al., "The membrane-cytoplasmic linker defines activity of FtsH proteases in Pseudomonas aeruginosa clone C," Journal of Biological Chemistry, vol. 300, no. 2, 2024.
[2]
M. Siegbahn et al., "Asymmetry in Cortical Thickness of the Heschl's Gyrus in Unilateral Ear Canal Atresia," Otology and Neurotology, vol. 45, no. 4, pp. 342-350, 2024.
[3]
B. Kataria et al., "Image quality in CT thorax: effect of altering reconstruction algorithm and tube load," Radiation Protection Dosimetry, vol. 200, no. 5, pp. 504-514, 2024.
[4]
T. Nordenfur, "Advancing Cardiovascular Shear Wave Elastography and Image Registration : Method Development and Safety Evaluation," Doctoral thesis : KTH Royal Institute of Technology, TRITA-CBH-FOU, 2024:16, 2024.
[5]
Z. Yang et al., "Lesion Localization in Digital Breast Tomosynthesis with Deformable Transformers by Using 2.5D Information," in Medical Imaging 2024: Computer-Aided Diagnosis, 2024.
[6]
H. Tomic et al., "Using simulated breast lesions based on Perlin noise for evaluation of lesion segmentation," in Medical Imaging 2024: Physics of Medical Imaging, 2024.
[7]
Z. Yang et al., "3D Breast Ultrasound Image Classification Using 2.5D Deep learning," in 17th International Workshop on Breast Imaging, IWBI 2024, 2024.
[9]
E. Bäcklin et al., "Pulmonary volumes and signs of chronic airflow limitation in quantitative computed tomography," Clinical Physiology and Functional Imaging, vol. 44, no. 4, pp. 340-348, 2024.
[11]
S. Persson and R. Moreno, "Bounding tractogram redundancy," Frontiers in Neuroscience, vol. 18, 2024.
[12]
S. Bendazzoli et al., "Lung vessel connectivity map as anatomical prior knowledge for deep learning-based lung lobe segmentation," Journal of Medical Imaging, vol. 11, no. 4, 2024.
[13]
[14]
M. Maleki et al., "New insights on cavitating flows over a microscale backward-facing step," Physics of fluids, vol. 36, no. 9, 2024.
[15]
M. Liden et al., "Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction," European Radiology, vol. 34, no. 1, pp. 39-49, 2024.
[16]
E. Breznik et al., "Cross-modality sub-image retrieval using contrastive multimodal image representations," Scientific Reports, vol. 14, no. 1, 2024.
[17]
T. Nilsson et al., "Acquisition Duration Optimization Using Visual Grading Regression in [68Ga]FAPI-46 PET Imaging of Oncologic Patients," Journal of Nuclear Medicine Technology, vol. 52, no. 3, pp. 221-228, 2024.
[19]
F. Sinzinger, "Geometric Deep Learning for Medical Image Processing Problems," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-CBH-FOU, 2024:48, 2024.
[20]
F. R. Talabazar et al., "Cavitation inception and evolution in cavitation on a chip devices at low upstream pressures," Physics of fluids, vol. 35, no. 1, 2023.
[21]
P. Bilic et al., "The Liver Tumor Segmentation Benchmark (LiTS)," Medical Image Analysis, vol. 84, pp. 102680, 2023.
[22]
K. Loskutova et al., "Biocompatibility of Cellulose Nanofiber-Coated Perfluoropentane Droplets," in The 28th European Symposium on Ultrasound Contrast Imaging, 2023.
[23]
K. Loskutova et al., "Cellulose Nanofiber-Coated Perfluoropentane Droplets: Fabrication and Biocompatibility Study," International Journal of Nanomedicine, vol. 18, pp. 1835-1847, 2023.
[24]
K. Loskutova, "Perfluorocarbon microdroplets stabilized by cellulose nanofibers : Toward ultrasound-mediated diagnostics and therapy," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-CBH-FOU, 2023:10, 2023.
[25]
A. Rosato et al., "Spontaneous Cardiac-Locomotor Coupling in Healthy Individuals During Daily Activities," in Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) : Volume 4: BIOSIGNALS, 2023, pp. 170-177.
[26]
J. Fu et al., "Fast three-dimensional image generation for healthy brain aging using diffeomorphic registration," Human Brain Mapping, vol. 44, no. 4, pp. 1289-1308, 2023.
[27]
A. Rosato et al., "Probability Of Cardiac-Locomotor Coupling During Daily Activities," in XXIX Congress of International Society of Biomechanics, ISB, Fukuoka, Japan, 2023.
[29]
R. Khan et al., "Dental image enhancement network for early diagnosis of oral dental disease," Scientific Reports, vol. 13, no. 1, 2023.
[30]
Y. Zhou et al., "Synthesis of Pediatric Brain Tumor Images With Mass Effect," in Medical Imaging 2023 : Image Processing, 2023.
[31]
K. Ahlgren et al., "New insights into the protein stabilizing effects of trehalose by comparing with sucrose," Physical Chemistry, Chemical Physics - PCCP, vol. 25, no. 32, pp. 21215-21226, 2023.
[32]
X. Song, G. Shen and D. Grishenkov, "A comparative study on detection of polymer-shelled microbubbles by different excitation pulses," Journal of the Acoustical Society of America, vol. 154, no. 1, pp. 482-493, 2023.
[33]
A. Hain, D. Jörgens and R. Moreno, "Randomized iterative spherical‐deconvolution informed tractogram filtering," NeuroImage, vol. 278, 2023.
[34]
[38]
F. Milosavljević et al., "The humanised CYP2C19 transgenic mouse exhibits cerebellar atrophy and movement impairment reminiscent of ataxia," Neuropathology and Applied Neurobiology, vol. 49, no. 1, 2023.
[39]
T. Nilsson et al., "A dose optimization study using Visual Grading Regression in [68Ga]-FAPI-46 PET imaging of patients with pancreatic lesions," European Journal of Nuclear Medicine and Molecular Imaging, vol. 50, no. SUPPL 1, pp. S493-S493, 2023.
[40]
W. Hager et al., "treatment outcome prediction from modeling the clinical target distribution for high-grade gliomas," Radiotherapy and Oncology, vol. 182, pp. S653-S654, 2023.
[41]
J. Xu et al., "Automatic segmentation of orbital wall from CT images via a thin wall region supervision-based multi-scale feature search network," International Journal of Computer Assisted Radiology and Surgery, vol. 18, no. 11, pp. 2051-2062, 2023.
[42]
C. Dartora et al., "A deep learning model for brain age prediction using minimally preprocessed T1w images as input," Frontiers in Aging Neuroscience, vol. 15, 2023.
[43]
F. R. Talabazar et al., "Chemical effects in "hydrodynamic cavitation on a chip" : The role of cavitating flow patterns," Chemical Engineering Journal, vol. 445, 2022.
[45]
I. Brusini, "Methods for the analysis and characterization of brain morphology from MRI images," Doctoral thesis Stockholm, Sweden : KTH Royal Institute of Technology, TRITA-CBH-FOU, 2022:9, 2022.
[46]
M. Platten, "Quantitative MRI Biomarkers of Neurodegeneration in Multiple Sclerosis," Doctoral thesis Stockholm : KTH, TRITA-CBH-FOU, 2022:10, 2022.
[47]
T. Abbasiasl et al., "A Flexible Cystoscope Based on Hydrodynamic Cavitation for Tumor Tissue Ablation," IEEE Transactions on Biomedical Engineering, vol. 69, no. 1, pp. 513-524, 2022.
[48]
[49]
E. Smedler et al., "Disrupted Cacna1c gene expression perturbs spontaneous Ca2+ activity causing abnormal brain development and increased anxiety," Proceedings of the National Academy of Sciences of the United States of America, vol. 119, no. 7, 2022.
[50]
K. Kisonaite et al., "Estimation of the cross-sectional surface area of the waist of the nerve fiber layer at the optic nerve head," in Progress in Biomedical Optics and Imaging : Proceedings of SPIE, 2022.