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All Journal International Journal of Electrical and Computer Engineering Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Journal of Electronics, Electromedical Engineering, and Medical Informatics Metalurgi
Asmaria, Talitha
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Astronomy Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Physics

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Finite Element Analysis of Patient Specific Bone Plate with Ti6Al4V Material Selection Asmaria, Talitha
Jurnal Penelitian Fisika dan Aplikasinya (JPFA) 2021: Articles in Press
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jpfa.v11n1.p%p

Abstract

A patient-specific implant is a designed implant that considers the needs of a specialized patient’s condition. In several surgical cases, the implant design needs to be adjusted based on the patient bone’s surface to suit the bone morphometry. This study aims to conduct the finite element analysis to investigate the stress distribution alongside the plate to consider clinical implementation. A bone plate has been designed following an adult pelvic bone shape for the pelvic fracture’s clinical case management. An FEA was accomplished to analyse the implant design’s performance and estimate the installation’s clinical failures before the manufacturing process. The FEA calculation achieved the highest number of von misses’ stresses (VM) on the pelvic bone plate by 3.616 MPa. The obtained VM number on the simulation is smaller than the yield strength of Ti6Al4V. It concludes that the customized iliac plate’s design using Ti6Al4V can have excellent mechanical strength and can withstand the loading. Additional similar simulation using another software strengthen the results.
Brain tumor detection using a MobileNetV2-SSD model with modified feature pyramid network levels Hikmah, Nada Fitrieyatul; Hajjanto, Ariq Dreiki; A. Surbakti, Armand Faris; Prakosa, Nadhira Anindyafitri; Asmaria, Talitha; Sardjono, Tri Arief
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp3995-4004

Abstract

Brain tumors, a subset of these malignancies, demand accurate and efficient diagnosis. Traditional methods use non-invasive medical imaging like magnetic resonance imaging (MRI) and computed tomography (CT). Although necessary for diagnosis, manual brain MRI picture segmentation is tedious and time-consuming. Using deep learning is a promising solution. This study proposes an innovative approach for brain tumor detection, focusing on meningioma tumors. Utilizing threshold-based segmentation, the MobileNetV2 architecture, a modified feature pyramid network (FPN), and single shot MultiBox detector (SSD), our model achieves precise localization and object detection. Pre-processing techniques such as grayscale conversion, histogram equalization, and Gaussian filtering enhance the MRI image quality. Morphological operations and thresholding facilitate tumor segmentation. Data augmentation and a meticulous dataset division aid in model generalization. The architecture combines MobileNetV2 as a feature extractor, SSD for object detection, and FPN for detecting small objects. Modifications, including lowering the minimum FPN level, enhance small object detection accuracy. The proposed model achieved a recall value of around 98% and a precision value of around 89%. Additionally, the proposed model achieved approximately 93% on both the dice similarity coefficient (DSC) value and the index of similarity. Based on the promising results, our research holds significant advancements for the field of medical imaging and tumor detection.
Convolutional neural network for assisting accuracy of personalized clavicle bone implant designs Mayasari, Dita Ayu; Hawari, Ihtifazhuddin; Dwiyanti, Sheba Atma; Noviyadi, Nathasya Reinelda; Andryani, Dinda Syaqila; Utomo, Muhammad Satrio; Hikmah, Nada Fitrieyatul; Asmaria, Talitha
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3208-3219

Abstract

The clavicle is a long bone that tends to be frequently fractured in the midshaft region. The plate and screw fixing method is mainly applied to address this issue. This study aims to construct a clavicle bone implant design with a consideration to achieve a high accuracy and high-quality surface between the plate and the clavicle surface. The computational tomography scanning (CT-scan) image series data were processed using a convolutional neural network (CNN) to classify the clavicle image. The CNN outcomes were gathered as three-dimensional (3D) volume data of clavicle bone. This 3D model was then proposed for the plate design. The CNN testing results of 97.4% for the image clavicle bones classification, whereas the prints of the 3D model from clavicle bone and its plate and screw design reveal compatibility between the bone surface and the plate surface. Overall, the CNN application to the series of CT images could ease the classification of clavicle bone images that would precisely construct the 3D model of clavicle bone and its suitable clavicle bone plate design. This study could contribute as a guideline for other bone plate areas that need to fit the patient’s bone geometry.
Comparative Studies Simulation Software for Bone Plate Compression Mayasari, Dita; Muhammad, Sirojuddin Kholil; Triwardono, Joko; Malau, Daniel Panghihutan; Utomo, Muhammad Satrio; Asmaria, Talitha
Metalurgi Vol 38, No 3 (2023): Metalurgi Vol. 38 No. 3 2023
Publisher : National Research and Innovation Agency (BRIN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/metalurgi.2023.738

Abstract

Medical applications occasionally require PSI (patient-specific implant) designs to match the implant bone’s geometry. To verify and predict failures of the design as well as a treatment before the manufacturing process, FEA (finite element analysis) is employed to simulate when given a specific number of loads. Plenty of studies have done the FEA using a couple of types of software; however, to the best of our knowledge, there is no literature to compare those several FEA results with a comparable experiment. This study further analyzes material stress, particularly to compute the VMS (Von Misses stress) of the Ti6Al4V bone plate. Furthermore, this study proposes to examine and deliver a comprehensive understanding using the four most used software of COMSOL, Ansys, Abaqus, and Autodesk Inventor. The results of those four simulations are then compared with the stress test through the Hardness Vickers test. This study will contribute significantly as a novel comparison between VMS and hardness test as a stress prediction in an implant material.  
From Imaging Data to Cranioplasty Implant Designs Asmaria, Talitha; Zain, Andi Justike Mahatmala; Pramesti, Arindha Reni; Marzuki, Azwien Niezam Hawalie; Utomo, Muhammad Satrio
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 5 No 3 (2023): July
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeemi.v5i3.300

Abstract

The cranioplasty procedure is starting from removal the skull bone defects and replacing them with any biocompatible material, such as polymer, ceramic, or titanium alloy. The complication of the surgery as well as the high cost from several material selection required a simulation. Besides that, the case of cranial defects sometimes required a customized design. The presence of three-dimensional (3D) printing technology would be a promising tool to improve the success rate. Prior to 3D printing, the model needs to be corrected from the initial patient’s imaging data to the intended implant design. However, previous related literatures were almost not informing the specific image processing steps to gain the models, while not all operators could understand this sophisticated technique. The study aims to design an implant bone for cranioplasty purpose. The data were processed through the very clear step-by-step image processing stages, three-dimensional (3D) printing, and its evaluation through biomechanical simulation. Quantitatively, the designed cranioplasty implant could deal with the load in the actual application. Qualitatively, the prototypes have matched if applied to the host of cranium bone. In conclusion, although image processing and refinements are the most complicated process, the whole explanation indicate that the provided precise methodology could be a major reference to the similar procedure.
Modelling of Human Cerebral Blood Vessels for Improved Surgical Training: Image Processing and 3D Printing Jacinda, Reica Diva; Yossy, Nebrisca Patriana; Menik Dwi Kurniatie; Hawar, Ihtifazhuddin; Setiawan, Andreas Wilson; Adidharma, Peter; Prasetya, Mustaqim; Desem, Muhammad Ibrahim; Asmaria, Talitha
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 1 (2025): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i1.583

Abstract

Human cerebral blood vessels are highly intricate and significantly contribute to brain function support. In the surgical process of these vessels, the neurosurgeons will basically employ magnetic resonance imaging (MRI) as an imaging media to understand the location of the disorder, the anatomical position of vessels, and a guide in the surgical process. However, the usage of MRI data remains a challenge for surgeons in understanding anatomical structures in greater detail, as well as the limitations of training in handling difficult cases. This study aims to provide further technology, combining three-dimensional (3D) image models and 3D printing to accommodate the lack of visualization and pre-operative simulation using MRI data. First, the MRI data would be exported to a software 3D slicer that has the ability to process images with a threshold method to segment the required body parts and generate 3D models. Then, the 3D model of blood vessels would be imprinted using the SLA method to provide the complex anatomical structures of blood vessels. The results from both 3D image modeling and 3D printing have been validated and have dimensions similar to those of the MRI data, indicating that this work is highly accurate. This work significantly helps the surgeons to have a better plan for the surgery steps, identify potential issues before the procedure begins, and develop more precise approaches.
Co-Authors A. Surbakti, Armand Faris Adidharma, Peter Andreas Wilson Setiawan Andryani, Dinda Syaqila Desem, Muhammad Ibrahim Dita Ayu Mayasari, Dita Ayu Dita Mayasari Dwiyanti, Sheba Atma Hajjanto, Ariq Dreiki Hawar, Ihtifazhuddin Hikmah, Nada Fitrieyatul Ihtifazhuddin Hawari Jacinda, Reica Diva Malau, Daniel Panghihutan Marzuki, Azwien Niezam Hawalie Menik Dwi Kurniatie Muhammad, Sirojuddin Kholil Noviyadi, Nathasya Reinelda Prakosa, Nadhira Anindyafitri Pramesti, Arindha Reni Prasetya, Mustaqim Tri Arief Sardjono Triwardono, Joko Utomo, Muhammad Satrio Yossy, Nebrisca Patriana Zain, Andi Justike Mahatmala