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VARIASI PENGGUNAAN REKONTRUSI ALGORITMA FBP, iDose4 DAN ITERATIVE MODEL RECONTRUCTION (IMR) TERHADAP KUALITAS CITRA MCST THORAK LOW DOSE UNTUK MENDETEKSI NODUL PARU Anikmah, Siti; Kartikasari, Yeti; Kurniawati, Ary
JRI (Jurnal Radiografer Indonesia) Vol. 3 No. 2 (2020)
Publisher : Perhimpunan Radiografer Indonesia (PARI)

Background: Pulmonary nodules are often found accidentally when thorax imaging is done. The size and rate of nodule growth are the most important predictors of imaging for malignancy. When the low dose protocol applied to the thorax MSCT will affect image quality, such as increased noise and decreased spatial resolution, so that the detection of nodules becomes less accurate. For noise limitation the reconstruction of the FBP, iDose4 and IMR algorithm is used. The purpose of this literature study is to evaluate variations in the FBP, iDose4 and IMR algorithm in improving image quality. Methods: This method is a qualitative research with a descriptive approach using comprehensive literatures studies Results: The result show that noise reduction is highest at IMR and lowest at FBP. The highest number of detected nodules on IMR especially for solid nodules < 4 mm and the lowest on FBP. Pathological findings with the best quality on IMR and quality are limited to FBP. Visibility of normal and abnormal findings, iDose4 is better than IMR and FBP especially for reticular patterns. Effective doses are reduced by 44 % to 59 % based on this literature study. In clinical practice, IMR shows the potential for pathological recovery at low dose level and IMR can improved measured image quality based on noise, high contrast spatial resolution and low contrast detectability. Conclusion: So IMR is the most effective algorithm applied for scanning low dose MSCT thorax for detection of pulmonary nodules.

Analisis Citra Virtual Non Contrast (VNC) Sebagai Alternatif Pengganti Citra True Non Contrast (TNC) Pada Pemeriksaan Ct Scan Abdomen Endriasari, Endriasari; Kurniawati, Ary; Masrochah, Siti
Jurnal Imejing Diagnostik (JImeD) Vol 11, No 2 (2025): JULY 2025
Publisher : Poltekkes Kemenkes Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31983/jimed.v11i2.13401

Background: Multiphase abdominal CT is a radiological imaging procedure using contrast media to detect abnormalities or diseases of internal abdominal organs. The development of Dual Energy CT (DECT) technology, particularly the liver VNC feature, enables the reconstruction of virtual non-contrast (VNC) images from post-contrast data, potentially eliminating the need for a true non-contrast (TNC) phase. This study aims to analyze anatomical information differences between TNC and VNC images and determine the most optimal image type for detecting abdominal masses.Methods: This research employed a quantitative experimental approach involving 10 patients who underwent multiphase abdominal CT at RSPAU Dr. Suhardi Hardjolukito. Comparative anatomical data between TNC and VNC images were evaluated by two radiology specialists. Inter-rater agreement was assessed using Cohen’s Kappa test, while the Wilcoxon test was used to analyze image information differences. To identify the most optimal anatomical image, the mean ranks of TNC and VNC were compared.Results: The results showed no significant anatomical information difference between VNC and TNC images in evaluating abdominal parenchyma, lesions, and vascularization, with a p-value of 0.083. In terms of mean rank, VNC had a value of 1.00, while TNC had 0.00, categorized as negative ranks, indicating that VNC was rated lower than TNC. Thus, the TNC algorithm is considered superior to VNC, even though most data showed no difference between the two image types.Conclusion: VNC images may serve as an alternative to TNC in multiphase abdominal CT, especially for abdominal mass cases. Future research is recommended to incorporate Hounsfield Unit (HU) and noise analysis and to consider integrating the VNC feature into dual-energy CT protocols.

Kajian Debit Banjir di Wilayah Sungai Saddang Kabupaten Pinrang Sulawesi Selatan dengan Menggunakan Grafik Creager Kurniawati, Ary; Musa, Ratna; Mallombassi, Ali; Wellang, Musafir
Jurnal Flyover Vol. 1 No. 2 (2021): Agustus - Januari
Publisher : Magister Teknik Sipil PPs UMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52103/jfo.v1i2.755

Dalam analisis banjir rancangan dengan pendekatan data hujan suatu wilayah seringkali terbentur oleh masalah kalibrasi pemilihan metode yang paling mendekati kondisi banjir aktual dilapangan sementara alat pengukur debit pada hampir semua sungai belum memadai. Sehingga diperlukan suatu model kalibrasi yang merupakan pendekatan dari debit banjir actual di lapangan. Salah satu model kalibrasi untuk debit banjir rancangan sungai adalah dengan metode grafik creager. Wilayah sungai saddang yang merupakan suatu wilayah sungai yang memiliki potensi sumberdaya air dan potensi bencana yang cukup besar di Sulawesi Selatan belum dilengkapi alat pencatatan debit yang cukup untuk semua Daerah Aliran Sungai didalamnya. Sehingga studi untuk membentuk model grafik creager di lakukan dengan menggunakan data actual banjir dari alat-alat pencatatan debit yang ada dilakukan. Dari data debit banjir dan luas DAS terbentuk grafik creager yang mewakili kondisi banjir di WS Saddang dengan Q100th, Q50th, Q25 th, Q10 tahun, Q5th dan Q2th. Sebagai pembanding dilakukan analisis perhitungan banjir dengan perhitungan kapasitas banjir penampang sungai asli dan beberapa metode hidrograf banjir dari pendekatan data hujan yaitu dengan hidrograf satuan sintetis Nakayasu, Snyder dan ITB 1 di salah satu DAS di WS. Saddang. Hasil perbandingan debit menunjukkan hasil debit banjir dari grafik creager mendekati hasil perhitungan debit dengan perhitungan kapasitas banjir penampang sungai asli dan didekati dengan cukup baik dengan hasil metode lainnya dengan penyimpangan terbesar 14,4% dengan metode ITB 1.

Penerapan Artificial Intelligence dalam Mendeteksi Batu Ginjal secara Otomatis pada Citra CT Scan Sulaksono, Nanang; Kurniawati, Ary
Jurnal Imejing Diagnostik (JImeD) Vol. 10 No. 1: JANUARY 2024
Publisher : Poltekkes Kemenkes Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31983/jimed.v10i1.11072

Background: Kidney stones are a clinical condition with the presence of stones along the urinary tract of varying sizes. The aim of this research is the need for a system to automatically detect kidney stones so that it can help radiologists in diagnosing kidney stones accurately, effectively and efficiently, and patients can immediately undergo further action to cure kidney stones.Methods: The difference in research carried out by researchers is the use of artificial intelligence which uses deep learning with a convolutional neural network (CNN) algorithm. This research uses images obtained from CT scan results from public data (Kaggle) and primary hospital data. The number of images used in the Augmentation training data was 2338 normal images and 2390 kidney stone images. The augmentation testing data used 540 normal images and 446 kidney stone images. The research also involved experts, namely radiology specialists, in determining images with abnormal and normal stone tones.Results: research obtained from CT Scan images of kidney stones with augmentation and original using public data/Kaggle images, obtained using augmentation obtained a high accuracy value of 99.69%. Meanwhile, in testing data using primary/hospital data images, augmented data obtained accuracy values that were still low at 45.43% and 45.23%, respectively.Conclusions: The use of deep learning with the CNN model in training data augmentation obtained high accuracy values, however in testing data using hospital CT scan images the accuracy value was still low, but it was able to recognize images of kidney stones, so it could help in automatically diagnosing kidney stones. For future work could involve refining the model to handle variations in hospital data or exploring additional features to improve generalizability.

Optimasi Informasi Diagnostik Citra Axial MRI Brain antara Sekuen SWI dan T2 FLASH 2D pada Kasus Tumor Otak Farida, Siti Nur; Sulaksono, Nanang; Kurniawati, Ary
Jurnal Imejing Diagnostik (JImeD) Vol. 10 No. 2 (2024): JULI 2024
Publisher : Poltekkes Kemenkes Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31983/jimed.v10i2.11583

Background: Pulse gradient echo sequences use varying RF excitation pulses and with NMV flips through various angles (not just 90Â°). Gradient echo has a sensitive susceptibility effect in detecting the presence of blood products (hemorrhage) and calcifications in brain tumors. The SWI and T2 FLASH 2D sequences are part of the pulse sequence gradient echo, where the SWI sequence is a 3D velocity compensated gradient echo and the T2 FLASH 2D sequence is a 2D multi-slice gradient echo. This study aims to determine the differences in axial image diagnostic information and determine the most optimal axial image diagnostic information in MRI brain examinations between SWI and T2 FLASH 2D sequences in brain tumor cases.Methods: This type of research is quantitative with an experimental approach. Data was taken in March 2024 at the Radiology Installation of RSUP Dr. Sardjito Yogyakarta. The sample in this study was 10 patients with brain tumor cases. An assessment was carried out by 2 respondents to assess the criteria for brain tumors. The assessment data from respondents was tested using the Cohen's kappa test to assess reliability between respondents and the Wilcoxon test to determine the level of difference in axial image diagnostic information, then the mean rank was used to determine sequences with better diagnostic image information.Results: The results of the study show that there is a difference in the diagnostic information of axial images on MRI brain examination between SWI and T2 FLASH 2D sequences in tumor cases with a p-value of 0.014. The significant difference is due to the susceptibility effect in both sequences. Based on the Wilcoxon test, the SWI sequence is the most optimal sequence in displaying diagnostic information with a mean rank value of 4.Conclusions: There is a difference of axial image diagnostic information between SWI and T2 FLASH 2D sequence in Brain MRI with brain tumors cases, and SWI sequence produces the most optimal axial image diagnostic information in MRI brain with brain tumor cases.

Analisis Citra Virtual Non Contrast (VNC) Sebagai Alternatif Pengganti Citra True Non Contrast (TNC) Pada Pemeriksaan Ct Scan Abdomen Endriasari, Endriasari; Kurniawati, Ary; Masrochah, Siti
Jurnal Imejing Diagnostik (JImeD) Vol. 11 No. 2 (2025): JULY 2025
Publisher : Poltekkes Kemenkes Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31983/jimed.v11i2.13401

Background: Multiphase abdominal CT is a radiological imaging procedure using contrast media to detect abnormalities or diseases of internal abdominal organs. The development of Dual Energy CT (DECT) technology, particularly the liver VNC feature, enables the reconstruction of virtual non-contrast (VNC) images from post-contrast data, potentially eliminating the need for a true non-contrast (TNC) phase. This study aims to analyze anatomical information differences between TNC and VNC images and determine the most optimal image type for detecting abdominal masses.Methods: This research employed a quantitative experimental approach involving 10 patients who underwent multiphase abdominal CT at RSPAU Dr. Suhardi Hardjolukito. Comparative anatomical data between TNC and VNC images were evaluated by two radiology specialists. Inter-rater agreement was assessed using Cohenâ€™s Kappa test, while the Wilcoxon test was used to analyze image information differences. To identify the most optimal anatomical image, the mean ranks of TNC and VNC were compared.Results: The results showed no significant anatomical information difference between VNC and TNC images in evaluating abdominal parenchyma, lesions, and vascularization, with a p-value of 0.083. In terms of mean rank, VNC had a value of 1.00, while TNC had 0.00, categorized as negative ranks, indicating that VNC was rated lower than TNC. Thus, the TNC algorithm is considered superior to VNC, even though most data showed no difference between the two image types.Conclusion: VNC images may serve as an alternative to TNC in multiphase abdominal CT, especially for abdominal mass cases. Future research is recommended to incorporate Hounsfield Unit (HU) and noise analysis and to consider integrating the VNC feature into dual-energy CT protocols.

Pelatihan Penggunaan Cairan Klorin Untuk Menurunkan Angka Mikroorganisme Pada Kaset Radiografi Kurniawati, Ary; Handoko, Bagus Dwi; Kurniawan, Andrey Nino
Madani : Indonesian Journal of Civil Society Vol. 6 No. 1 (2024): Madani : Februari 2024
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/madani.v6i1.1845

Radiography has an important role in diagnosing a patient's disease, but the equipment used has a considerable risk as a place for the development of nosocomial bacteria which can endanger the patient and radiographer. Cassettes, one of the tools in radiography, have the potential to become a medium for disease transmission and based on previous research it has been proven that there are microorganisms and fungi on the cassettes, so the cassettes need to be cleaned regularly. One of the duties of a radiographer in the field of radiology services is the management of radiology equipment facilities and infrastructure. Cleaning the cassette with 70% alcohol can reduce the number of microorganisms on its surface. The methods in this activity are lectures, simulations, and practice cleaning cassettes with chlorine. The activities were carried out at the Laboratory of the Department of Radiodiagnosis and Radiotherapy Technique at the Semarang Health Polytechnic Ministry with radiographers from hospitals and clinical laboratories in the city of Semarang. The activity begins with the registration, opening, delivering material to the participants, and the simulation of resource persons. Evaluation is done by filling in the pretest and posttest. The evaluation results showed an increase in participants' knowledge of 63% about how to clean cassettes using liquid chlorine to reduce the number of microorganisms on radiographic cassettes. With this training, radiographers are expected to be able to apply cleaning radiographic cassettes with liquid chlorine 0,5% in their respective institutions.

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