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"Trauma kepala merupakan cedera fisik pada jaringan otak yang secara sementara atau permanen merusak fungsi otak. Salah satu akibat yang dapat disebabkan oleh trauma kepala adalah perdarahan intrakranial. Perdarahan intrakranial perlu didiagnosis dengan mengambil gambar computed tomography (CT) scan oleh dokter radiolog. Setelah itu dokter radiolog akan mensegmentasi dan menghitung volume perdarahan pada gambar CT scan untuk menentukan Tindakan selanjutnya. Namun, pada beberapa rumah sakit di Indonesia, kurangnya sumber daya dokter yang dapat menafsirkan hasil CT scan dapat menyebabkan morbiditas dan mortalitas pasien perdarahan intrakranial. Algoritma deep learning, di antaranya convolutional neural networks (CNN) dapat digunakan untuk membantu dokter untuk mensegmentasi dan menghitung volume perdarahan intrakranial. Pada penelitian ini, penulis mengusulkan segmentasi otomatis dan aproksimasi volume perdarahan pada penderita perdarahan intrakranial dengan menggunakan metode deep learning dan regresi. Segmentasi perdarahan dilakukan dengan menggunakan arsitektur Dynamic Graph Convolutional Neural Network (DGCNN) sementara perhitungan volume perdarahan dilakukan dengan menggunakan beberapa metode regresi. Data pasien perdarahan intrakranial diperoleh dari rumah sakit Cipto Mangunkusumo yang telah disegmentasi secara manual oleh dokter radiolog. Pada segmentasi perdarahan, dibuat beberapa skenario dengan melakukan up sampling dan down sampling pada data. Hasil terbaik didapatkan pada skenario tanpa melakukan up sampling menghasilkan sensitivitas 97,8% dan spesifisitas 95,6%. Pada aproksimasi volume perdarahan, hasil terbaik didapatkan dengan menggunakan metode support vector machine (SVM) dengan kernel radial basis function (RBF) dengan mean squared error (MSE) 3,67 x 104.

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Traumatic brain injury is a common injury that can range from mild concussions to severe permanent brain damage. One of the severe damages caused by traumatic brain injury is intracranial hemorrhage, which is typically diagnosed by clinicians using head computed tomography (CT) scans. However, in some hospitals in Indonesia, sometimes there is a lack of clinicians who are able to interpret the CT scan results, leading to morbidity and mortality. Deep learning algorithms, especially convolutional neural networks (CNN) can be utilized to help clinicians in diagnosing patients with intracranial hemorrhage. In this study, we propose an automated segmentation and blood volume approximation of intracranial hemorrhage patients from CT scan images using deep learning and regression methods. For the blood segmentation, we utilized Dynamic Graph Convolutional Neural Network (DGCNN) architecture and for the blood volume approximation, we utilized regression methods. The dataset for this work consists of 27 head CT scans obtained from the Cipto Mangunkusumo National General Hospital 2019 traumatic brain injury data segmented manually by a radiologist. For blood segmentation, we proposed several scenarios by up sampling or down sampling the data. The best results obtained in the scenario without doing up sampling resulted in a sensitivity of 97.8% and a specificity of 95.6%. For blood volume approximation, the best results are obtained using the support vector machine (SVM) method with a radial basis function (RBF) kernel, with a mean squared error of 3.67 x 104."

"Computed Tomography (CT) Scanner merupakan alat pencitraan diagnostik yang memberikan informasi citra medis untuk menunjang pengobatan pasien, namun tanpa disadari pemanfaatan radiasinya dapat menimbulkan efek negatif pada organ sensitif sekitar. Penelitian ini dilakukan untuk mengukur dosis organ sensitif (mata, tiroid, dan payudara) menggunakan fantom Rando pada CT Scanner area thorax. Untuk memudahkan penelitian ini, TLD rod 100 digunakan sebagai dosimeter, dimana kV dan pitch dijadikan sebagai variasi parameter penelitian. Hasil menunjukkan bahwa nilai paparan dosis tertinggi pada tiap kualitas berkas berturut-turut dari 80, 120, dan 140 kV yaitu payudara kanan (1,72±0,34 mGy), tiroid kanan (6,25±0,16 mGy), dan payudara kiri (10,78±0,76 mGy). Pada variasi pitch nilai paparan dosis tertinggi secara berturut-turut dari 4, 6, dan 8 yaitu payudara kiri (6,19±0,02 mGy), tiroid kanan (6,25±0,16 mGy), dan payudara kanan (5,08±0,85 mGy). Dapat disimpulkan bahwa nilai dosis payudara pada CT Thorax lebih tinggi dibandingkan dengan mamografi, namun keduanya tidak melebihi nilai batas dosis yang ditetapkan International Commission on Radiological Protection (ICRP) yaitu 5 Gy.

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Computed Tomography (CT) Scanner is an instrument of medical imaging using radiation to support treatment for patient, but the radiation may give a negative effect around sensitive organs. The research meant to measure dose for sensitive organs at thorax area (eyes, thyroid, and breast) using CT Scanner with rando phantom as an object. To ease this experiment, TLD rod 100 used as dosimetry, which kV and pitch as a parameter variation. The result showed that the highest dose for kV variation upon each sequent beam quality from 80, 120, and 140 kV are right breast (1,72±0,34 mGy), right thyroid (6,25±0,16 mGy), and left breast (10,78±0,76 mGy). Towards pitch variation the highest exposure dose value in sequently from 4, 6, and 8 are left breast (6,19±0,02 mGy), right thyroid (6,25±0,16 mGy), and right breast (5,08±0,85 mGy). As a conclusion, the dose on breast from CT Thorax is higher than the one from mammography but both are bellow dose value limit from International Commission on Radiological Protection (ICRP) which is 5 Gy."

"Pemeriksaan yang paling tepat dalam menentukan volume jaringan lemak visceral dilakukan dengan menggunakan modalitas CT-scan. Namun karena setiap slice citra memiliki bentuk dan lokasi lemak visceral yang berbeda-beda, maka penentuan volume menjadi tidak mudah. Sehingga, Computer Aided Diagnosis (CAD) dapat dijadikan salah satu solusi untuk membantu tenaga ahli dalam pembacaan citra dan menganalisa area lemak terutama area lemak visceral pada citra abdomen dengan lebih akurat. Dalam penelitian ini, sistem CAD dikembangkan dengan menggunakan metode segmentasi Thresholding, ekstrasi ciri berbasis Gray Level Co-Occurrence Matrix (GLCM) dan klasifikasi citra lemak visceral menggunakan Multilayer Perceptron (MLP). Penelitian ini mengolah data 665 citra CT-scan abdomen dari 38 pasien yang diperoleh dari Rumah Sakit Persahabatan Jakarta. Data tersebut dibagi menjadi 70% citra sebagai data pelatihan dan 30% citra sebagai data pengujian. Hasil performa sistem CAD yang direpresentasikan sebagai tingkat keakurasian dengan nilai sebesar 98.73% untuk data pelatihan dan 95.58% untuk data pengujian. Selain itu, juga diperoleh informasi bahwa hasil kalkulasi volume area jaringan lemak visceral dengan nilai terbesar yaitu sebesar 1238.89 dengan tebal slice sebesar 5 mm. Sedangkan ketebalan 10 mm diperoleh volume sebesar 1072.91 Sementara untuk hasil kalkulasi volume area jaringan lemak visceral terkecil sebesar 107.57 pada ketebalan 5 mm. Sedangkan ketebalan 10 mm diperoleh volume sebesar 47.43 . Evaluasi pada proses segmentasi dilakukan menggunakan metode SSIM dengan mengahasilkan nilai rata-rata SSIM untuk keseluruhan data sebesar 0.843 pada data latih dan 0.838 pada data uji. Dari hasil penelitian ini, sistem CAD berhasil dikembangkan untuk membantu dalam proses mengestimasi volume area jaringan lemak visceral. Namun, tingkat keakurasian antara kalkulasi volume lemak visceral menggunakan sistem CAD dan software CT-scan belum dapat diperoleh dengan baik.

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The most precise examination in determining the volume of abdominal fat tissue is using a CT-scan modality. However, because each slice image has a different shape and location of visceral fat, it is not easy to determine the volume. So that, Computer Aided Diagnosis (CAD) can be used as a solution to assist experts in reading images and analyzing fat areas, especially visceral fat areas on abdominal images more accurate. In this study, a CAD system was developed using the Thresholding segmentation method, feature extraction based on Gray Level Co-Occurrence Matrix (GLCM) for the identification of abdominal fat. Next, in the classification process, the visceral fat area is separated from the subcutaneous fat area using Multilayer Perceptron (MLP). This study processed data from 665 abdominal CT-scan images from 38 patients obtained from Persahabatan Hospital. The data is divided into 70% images as training data and 30% images as test data. The results of the CAD system performance are represented as the level of accuracy with a value of 98.73% for training data and 95.58% for test data. In addition, information was also obtained that the calculation of the volume of visceral fat tissue areas with the largest value of 1238.89 with a slice thickness of 5 mm. While the thickness of 10 mm obtained a volume of 1072.91 Calculation of the volume of the volume area of ​​the smallest visceral fat tissue of 107.57 at 5 mm thickness. While the thickness of 10 mm obtained a volume of 47.43 . Evaluation of the segmentation process was carried out using the SSIM method by producing an average SSIM value for the entire data of 0.843 in the training data and 0.838 in the test data. From the results of this study, a CAD system was successfully developed to assist in the process of estimating the volume of visceral fat tissue area. However, the level of accuracy between the calculation of visceral fat volume using CAD systems and CT-scan software has not been obtained properly.

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"Pendahuluan : Insidensi pembesaran kelenjar prostat mencapai 50% pada pria berusia 50 tahun keatas. Berbagai modalitas pemeriksaan radiologi memiliki sensitifitas yang berbedabeda dalam estimasi volume kelenjar prostat. Modalitas yang paling tersedia di Indonesia pada layanan kesehatan adalah USG transabdominal dan Computed tomography scan (CT scan). Tujuan : Menilai korelasi modalitas USG transabdominal dan CT scan dalam estimasi ukuran volume kelenjar prostat. Metode : Studi korelasi dilakukan pada pasien pria berusia diatas 50 tahun keatas yang menjalani pemeriksaan CT scan whole abdomen dan dilakukan pengukuran volume kelenjar prostat dengan USG transabdominal. Setiap dimensi ukuran kelenjar prostat dan volume merupakan data numerik terdistribusi tidak normal, sehingga digunakan uji Spearman. Hasil : Dari 23 subjek penelitian, didapatkan korelasi dimensi panjang (r=0,53, p=0,01), dimensi lebar (r=0,81, p=0,00), dan dimensi tinggi (r=0,64, p=0,001) yang signifikan. Untuk korelasi volume kelenjar prostat (r=0,80, p=0,000) didapatkan signifikan. Kesimpulan : Terdapat korelasi yang signifikan pada setiap ukuran dimensi kelenjar prostat dan volume yang didapatkan.

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Introduction : Prostate gland enlargement incidence about 50% in male population age 50 years and above. There are so many radiology modalities with difference sensitifity in estimating prostate volume. The most available modalities in Indonesian health care services are transabdominal sonography and computed tomography scan (CT scan).

Objective : Assessing correlation in both modalities in evaluating prostate volume measurement.

Methods : Correlation study was done in male ages 50 years and above underwent whole abdominal CT scan and prostate gland were measured by transabdominal sonography. Both numeric data were abnormal distribution, so Spearman test was done.

Results : There are significant correlation either between length (r=0,53, p=0,01), wide (r=0,81, p=0,00), and height dimensions (r=0,64, p=0,001) or volume measurement (r=0,80, p=0,000) in 23 subjects.

Conclusions : Significant correlation either in each prostate dimension or prostate volume measurement."

"X-ray computed tomography (CT) has been playing an important role in current medical practice for diagnostic procedure. Beside its delicate technology, the 'hidden' software of CT image reconstruction has contributed almost half of total cost of a CT-scanner unit. Since Algebraic Reconstruction Technique (ART) is a basic to understand an iterative method of CT image reconstruction algortihm, and since it is difficult to find a clear description of fan beam ART algorithm in university literatures, it is important to develop an own algorithm and to begin a basic systematic research of this iterative method. After a long term of trial and error work, the research had succeded in developing an ART algorithm for third generation CT image reconstruction. By comparing the result of the research with more popular technique like Filtered Back Projection (FBP), the algorithm has been proved applicable to reconstruct a low dimension object matrix (32x32 and 64x64). By the resulted computer program, then basically a simple and low cost third generation CT-scanner can be designed for medical physics or biomedical imaging research. Finding a way of shortening the massive number of iterations process then, will be able to open the possibility of using the software for higher object matrix dimensions."

"Computed Tomography Dose Index (CTDI) merupakan konsep utama dalam dosimetri CT scan. Berdasarkan rekomendasi IAEA di TRS 457, CTDI dapat diukur di udara dan di fantom khusus CTDI. Ukuran dan massa fantom cukup besar sehingga akan menyulitkan dalam mobilisasi. Dalam penelitian ini dilakukan pengukuran CTDI untuk mengetahui faktor fantom pesawat Siemens Sensation 64. Faktor fantom adalah perbandingan CTDIw terhadap CTDIair. Fantom yang digunakan adalah fantom berbahan polymethil methacrylic (PMMA) berdiameter 16 cm sebagai fantom kepala dan 32 cm sebagai fantom tubuh. Detektor yang digunakan adalah Xi CT Platinum dan Xi Base Unit sebagai elektrometer. Estimasi dosis efektif dihitung berdasarkan nilai CTDIair pengukuran yang dikoreksi dengan perangkat lunak ImPACT CT Dosimetry Patient Calculator version 1.0.4. Nilai faktor fantom yang diperoleh untuk fantom kepala dan tubuh secara berturut-turut ialah 0.702 dan 0.357. Estimasi dosis efektif satu fase (rata-rata ± deviasi standar) ialah: kepala rutin 2.01 ± 0.11 mSv, kepala trauma 2.53 ± 0.16 mSv, thorak 3.4 2 ± 0.79 mSv, abdomen 5.99 ± 2.16 mSv, dan pelvis 2.12 ± 0.99 mSv. Faktor konversi DLP displai scanner terhadap dosis efektif: kepala rutin 0.0021 mSv/mGy.cm, kepala trauma 0.0022 mGy.cm, thorak 0.0182 mSv/mGy.cm, abdomen 0.0151 mSv/mGy.cm, dan pelvis 0.0118 mSv/mGy.cm.

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Computed Tomography Dose Index (CTDI) is primary dosimetric concept in CT scan. Based on IAEA TRS 457 recommendation, CTDI can be measured free in air and by using phantom. Phantom size and mass are huge, thus it will complicate the mobilization. This research conducted CTDI measurement to find out the Siemens Sensation 64 phantom factor. Phantom factor is a ratio between CTDIw over CTDIair. A Polymethyl Methacrylic (PMMA) phantom was used in this research, which has 16 cm of diameter for head phantom and 32 cm of diameter for body phantom. The Xi CT Platinum detector was used in this research and Xi base unit is as an electrometer. The estimation of effective dose was calculated using CTDIair value and ImPACT CT Dosimetry Patient Calculator version 1.0.4. In this research was found out that the phantom factors are 0.702 for head phantom and 0.357 for body phantom. The estimation of effective dose for one phase (mean ± standard deviation): head routine 2.01 ± 0.11 mSv, head trauma 2.53 ± 0.16 mSv, thorax 3.4 2 ± 0.79 mSv, abdomen 5.99 ± 2.16 mSv, and pelvis 2.12 ± 0.99 mSv. DLP on scanner display to effective dose conversion factors: head routine 0.0021 mSv/mGy.cm, head trauma 0.0022 mSv/mGy.cm, thorax 0.0182 mSv/mGy.cm, abdomen 0.0151 mSv/mGy.cm, and pelvis 0.0118 mSv/mGy.cm."

"Tujuan: Penelitian ini dilakukan untuk mendapatkan data profil kanalis fallopii segmen mastoid dan korda timpani sebelum operasi mastoidektomi untuk mengurangi angka morbiditas cedera kanalis fallopii akibat operasi. Metode: Pada penelitian retrospektif ini dilakukan rekonstruksi High-Resolution Computed Tomography tulang temporal terhadap 100 tulang temporal normal pada 50 pasien yang menjalani pemeriksaan CT scan kepala dan leher, yang diambil dari raw-data mulai Desember 2012 sampai Februari 2013. Rekonstruksi dilakukan dengan parameter ketebalan irisan 0,6 cm, increment 0,3 cm, Kernel filter Very Sharp (H70s), Window setting Osteo/Mastoid, menggunakan pesawat MDCT Somatom Definition Flash Dual Source 128 slice. Hasil dan diskusi: Bentuk kanalis fallopii segmen mastoid paling banyak ditemukan tipe lurus sebanyak 75%, defleksi terhadap bidang sagital dan defleksi terhadap bidang horizontal anatomi paling banyak ditemukan tidak terdapat defleksi sebanyak 62% dan 68%. Percabangan korda timpani paling banyak ditemukan intratemporal sebanyak 75%, yang tersering pada 1/3 distal kanalis fallopii segmen mastoid. Sudut korda timpani yang dibentuk korda timpani terhadap kanalis fallopii segmen mastoid paling banyak ditemukan antara 16 sampai 30 derajat sebanyak 37,3%. Ukuran korda timpani yang minimal tervisualisasi adalah 0,04 cm. Kesimpulan: Proporsi defleksi kanalis fallopii segmen mastoid terhadap bidang sagital dan horizontal adalah tidak terdapat defleksi.

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Objectives: This research was conducted to obtain profile data of mastoid segment of fallopian canal and tympanic cord before masteidectomy to reduce the morbidity rate of surgery-related fallopian canal injury.

Material and method: In this retrospective study reconstruction of High Resolution Computed Tomography of the temporal bone in 100 normal temporal bone in 50 patients who underwent a CT scan of the head and neck, were taken from the raw-data from December 2012 to February 2013. Reconstruction is done by parameters slice thickness 0,6 cm, increment 0,3 cm, Kernel filter Very Sharp (H70s), Window setting Osteo/Mastoid,using MDCT Somatom Definition Flash Dual Source 128 slice.

Result: Mastoid segment of fallopian canal commonly found type of straight as much as 75%, deflection of the sagittal plane and the horizontal field of anatomy most commonly found there was no deflection were 62% and 68%, respectively. Branching chordate tympani most commonly found intratemporal as much as 75%, which is common in 1/3 distal of mastoid segmen fallopian canal. The angled formed by chorda tympani and mastoid segment fallopian canal is most prevalent among 16 to 30 degrees as much as 37.3%. The minimum size of the chorda tympani is 0.04 cm.

Conclusion: Proportion of deflection mastoid segment facial canal of the sagittal and horizontal plane there is no deflection."

""The book offers a comprehensive and user-oriented description of the theoretical and technical system fundamentals of computed tomography (CT) for a wide readership, from conventional single-slice acquisitions to volume acquisition with multi-slice and cone-beam spiral CT. It covers in detail all characteristic parameters relevant for image quality and all performance features significant for clinical application. Readers will thus be informed how to use a CT system to an optimum depending on the different diagnostic requirements. This includes a detailed discussion about the dose required and about dose measurements as well as how to reduce dose in CT. All considerations pay special attention to spiral CT and to new developments towards advanced multi-slice and cone-beam CT. For the third edition most of the contents have been updated and latest topics like dual source CT, dual energy CT, flat detector CT and interventional CT have been added. The enclosed CD-ROM again offers copies of all figures in the book and attractive case studies, including many examples from the most recent 64-slice acquisitions, and interactive exercises for image viewing and manipulation. This book is intended for all those who work daily, regularly or even only occasionally with CT: physicians, radiographers, engineers, technicians and physicists. A glossary describes all the important technical terms in alphabetical order. The enclosed DVD again offers attractive case studies, including many examples from the most recent 64-slice acquisitions, and interactive exercises for image viewing and manipulation"--Back cover."

"Perkiraan nilai dosis yang diterima pasien ( CTDI ) yang langsung ditampilkan pada monitor CT setiap selesai pemeriksaan akan diketahui ketepatan nilainya dengan pengukuran langsung menggunakan pencil ion chamber dan pengukuran tidak langsung menggunakan TLD (Thermolumescence Dosimeter ) yang ditempatkan pada objek phantom dan dibandingkan dengan nilai dosis referensi yang telah ditetapkan, sehingga diharapkan mendapatkan informasi nilai dosis yang sebenarnya.Analisis variasi parameter kV, mAs, dan pitch untuk menentukan berapa rentang nilai parameter optimum untuk mendapatkan nilai dosis pasien (CTDI/mAs) yang minimum namun tidak mengesampingkan kualitas pencitraan hasil CT. Scan yang baik guna menunjang diagnosa, pengukuran langsung maupun tidak langsung dengan menggunakan fantom kepala dan perut.Pengukuran tidak langsung dengan menggunakan TLD (Thermolumescence Dosimeter ) pada menunjukan hasil yang tidak jauh berbeda dengan pengukuran langsung dengan menggunakan pencil ion chamber, dapat ditunjukkan dengan hubungan sifat kelinearan antara pitch dan dosis (CTDI/mAs).

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An estimation dose (CTDI) received by the patient which is directly displayed on the CT monitor on every examination will be able to known it?s precisien by direct measurement using pencil ion chamber and the indirect measurement using TLD placed on the object (phantom) and compared with the value of dose reference, so the real dose rate will be known.

The variant analysis of kV, mAs and pitch parameters to justify the range of optimal parameter value, it is used to get the minimum patient dose rate (CTDI/mAs) while the image quality for supporting the diagnose still on the right value, directly or not directly using head and abdomen phantom.

Indirect measurement using TLD show unsignificant result if compared with the ion chamber. This value is shown by a relative variant parameter using stright pitch and dose ( CTDI/mAs)."

"Latar Belakang : Tebal ramus mandibula merupakan salah satu faktor penting yang harus diperhatikan saat melakukan Bilateral Sagittal Split Osteotomy BSSO . Fraktur unvaforable atau bad split dapat terjadi saat melakukan BSSO apabila ramus mandibula tipis. Data antropometri tentang tebal ramus mandibula masih belum banyak diteliti. Data antropometri tentang tebal ramus mandibula bisa dipakai sebagai acuan jika akan melakukan BSSO. Tujuan : untuk mengetahui tebal ramus mandibula berdasarkan CBCT Scan sebagai acuan tindakan BSSO. Metode : Subjek penelitian ini terdiri dari 61 sampel data DICOM CBCT Scan yang kemudian dilakukan reorientasi dalam 3 bidang dan dilakukan pengukuran pada tebal ramus mandibula menggunakan software Osirix LXIV. Hasil : Didapatkan rata-rata tebal ramus mandibula pada laki-laki 8.049 1.205 mm dan pada perempuan 8.463 1.358 mm. Pada kelompok usia 18-30 tahun didapatkan rata-rata tebal ramus mandibula 8.087 1.29 mm, kelompok usia 31-40 tahun 8.176 1.49 mm, kelompok usia 41-50 tahun 8.742 1.04 mm. Kesimpulan : Berdasarkan CBCT Scan, secara statistik tidak terdapat perbedaan yang bermakna tebal ramus mandibula pada jenis kelamin laki-laki dan perempuan maupun pada kelompok usia.

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Backgorund: Ramus mandibular thickness is one of the most important factor that has to be concerned when performing Bilateral Sagittal Split Osteotomy BSSO . Unfavorable fracture or bad split could happen when performing BSSO if the ramus mandible thickness is thin. There only a few regarding antropometric data about thickness of mandibular ramus.

Objective: To measure thickness of mandibular ramus based on CBCT Scan as a reference when performing BSSO.

Methods: Subject of this research consist of 61 data sample DICOM CBCT Scan which reoriented in three planes and measuring thickness of the ramus mandible using Osirix LXIV.

Result: Mean thickness of the ramus mandible for male is 8.049 1.205 mm and female 8.463 1.358 mm. In group age of 18 30 mean thickness of the ramus mandible is 8.087 1.29 mm, group age 31 40 is 8.176 1.49 mm, group age 41 50 is 8.742 1.04 mm.

Conclusion: Based on CBCT Scan there are no difference statistically between thickness of ramus mandible in male and female, and group of age."